My eyes, they burn! Also runs faster, slightly less buggy.
[ipdf/code.git] / tools / analysis.ipynb
1 {
2  "metadata": {
3   "name": ""
4  },
5  "nbformat": 3,
6  "nbformat_minor": 0,
7  "worksheets": [
8   {
9    "cells": [
10     {
11      "cell_type": "code",
12      "collapsed": false,
13      "input": [
14       "%pylab inline"
15      ],
16      "language": "python",
17      "metadata": {},
18      "outputs": [
19       {
20        "output_type": "stream",
21        "stream": "stdout",
22        "text": [
23         "Populating the interactive namespace from numpy and matplotlib\n"
24        ]
25       }
26      ],
27      "prompt_number": 3
28     },
29     {
30      "cell_type": "code",
31      "collapsed": false,
32      "input": [
33       "!pkill -9 ipdf"
34      ],
35      "language": "python",
36      "metadata": {},
37      "outputs": [],
38      "prompt_number": 62
39     },
40     {
41      "cell_type": "code",
42      "collapsed": false,
43      "input": [
44       "from common import *\n",
45       "import build\n",
46       "import scaling"
47      ],
48      "language": "python",
49      "metadata": {},
50      "outputs": [],
51      "prompt_number": 137
52     },
53     {
54      "cell_type": "code",
55      "collapsed": false,
56      "input": [
57       "# If things are changed run this instead of restarting kernel\n",
58       "scaling = reload(scaling)\n",
59       "build = reload(build)"
60      ],
61      "language": "python",
62      "metadata": {},
63      "outputs": [],
64      "prompt_number": 190
65     },
66     {
67      "cell_type": "markdown",
68      "metadata": {},
69      "source": [
70       "# Compile programs\n",
71       "\n",
72       "Build for each type of real, then save a local copy of the executable."
73      ]
74     },
75     {
76      "cell_type": "code",
77      "collapsed": false,
78      "input": [
79       "options[\"tobuild\"] += [\"mpfrc++\"]"
80      ],
81      "language": "python",
82      "metadata": {},
83      "outputs": [],
84      "prompt_number": 46
85     },
86     {
87      "cell_type": "code",
88      "collapsed": false,
89      "input": [
90       "build.BuildAll()"
91      ],
92      "language": "python",
93      "metadata": {},
94      "outputs": [
95       {
96        "output_type": "stream",
97        "stream": "stdout",
98        "text": [
99         "Building: ['single', 'double', 'GMPrat', 'mpfrc++']\n",
100         "\r",
101         "[                  0%                  ]"
102        ]
103       },
104       {
105        "output_type": "stream",
106        "stream": "stdout",
107        "text": [
108         " \r",
109         "[**********       25%                  ]  1 of 4 complete"
110        ]
111       },
112       {
113        "output_type": "stream",
114        "stream": "stdout",
115        "text": [
116         " \r",
117         "[*****************50%                  ]  2 of 4 complete"
118        ]
119       },
120       {
121        "metadata": {},
122        "output_type": "display_data",
123        "text": [
124         "'Failed to build GMPrat'"
125        ]
126       },
127       {
128        "output_type": "stream",
129        "stream": "stdout",
130        "text": [
131         " \r",
132         "[*****************75%*********         ]  3 of 4 complete"
133        ]
134       },
135       {
136        "output_type": "stream",
137        "stream": "stdout",
138        "text": [
139         " \r",
140         "[****************100%******************]  4 of 4 complete"
141        ]
142       },
143       {
144        "output_type": "stream",
145        "stream": "stdout",
146        "text": [
147         "\n"
148        ]
149       }
150      ],
151      "prompt_number": 47
152     },
153     {
154      "cell_type": "code",
155      "collapsed": false,
156      "input": [
157       "options[\"built\"] = [\"single\", \"double\", \"cumul-single\", \"cumul-double\", \"path-single\", \"path-double\", \"path-rat\"] # Hack for now, these were manually compiled"
158      ],
159      "language": "python",
160      "metadata": {},
161      "outputs": [],
162      "prompt_number": 91
163     },
164     {
165      "cell_type": "markdown",
166      "metadata": {},
167      "source": [
168       "# Accuracy of Rendering VS Scaling"
169      ]
170     },
171     {
172      "cell_type": "code",
173      "collapsed": false,
174      "input": [
175       "scaling_data = {}\n",
176       "for b in options[\"built\"]:\n",
177       "    scaling_data[b] = scaling.FixedScales(\"./\"+b, fps=100, xz=0.5, yz=0.5)\n",
178       "    "
179      ],
180      "language": "python",
181      "metadata": {},
182      "outputs": [],
183      "prompt_number": 92
184     },
185     {
186      "cell_type": "markdown",
187      "metadata": {},
188      "source": [
189       "<table>\n",
190       "    <tr><td><b>Original</b></td><td><b>Scaled</b></td></tr>\n",
191       "    <tr><td><img src=\"original.bmp\" width=\"50%\"/></td><td><img src=\"final.bmp\" width=\"50%\"/></td></tr>\n",
192       "</table>"
193      ]
194     },
195     {
196      "cell_type": "code",
197      "collapsed": false,
198      "input": [
199       "fig = figure(figsize=(6,4))\n",
200       "for b in scaling_data:\n",
201       "    plot(1.0/scaling_data[b][\"accuracy\"][:,2], scaling_data[b][\"accuracy\"][:,5])\n",
202       "xscale(\"log\")\n",
203       "legend(scaling_data.keys(), loc=\"best\")\n",
204       "title(\"Loss of Precision for a 1x1 pixel grid\\nView Top Left: (0.5,0.5)\")\n",
205       "xlabel(\"Magnification (1/width)\")\n",
206       "ylabel(\"Representable Lines\")\n",
207       "\n",
208       "fig.savefig('../../sam/figures/loss_of_precision_grid_0.5.pdf', format='PDF')"
209      ],
210      "language": "python",
211      "metadata": {},
212      "outputs": [
213       {
214        "metadata": {},
215        "output_type": "display_data",
216 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pTmQrQ56qgmRDWNJYgRI0bA2NhY4djo0aMhFNZW+Y9//AOZmbU7ep08eRI+Pj7Q0dGBXC6Hg4MD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\n",
217        "text": [
218         "<matplotlib.figure.Figure at 0x7f305427d810>"
219        ]
220       }
221      ],
222      "prompt_number": 97
223     },
224     {
225      "cell_type": "code",
226      "collapsed": false,
227      "input": [
228       "fig = figure(figsize=(6,4))\n",
229       "for b in scaling_data:\n",
230       "    plot(1.0/scaling_data[b][\"accuracy\"][:,2], scaling_data[b][\"performance\"][:,3])\n",
231       "xscale(\"log\")\n",
232       "legend(scaling_data.keys())\n",
233       "xlabel(\"Magnification\")\n",
234       "ylabel(\"Average FPS (100 frames)\")"
235      ],
236      "language": "python",
237      "metadata": {},
238      "outputs": [
239       {
240        "metadata": {},
241        "output_type": "pyout",
242        "prompt_number": 98,
243        "text": [
244         "<matplotlib.text.Text at 0x7f3053e62150>"
245        ]
246       },
247       {
248        "metadata": {},
249        "output_type": "display_data",
250 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uDVdPeKOwXrBFPslliytLQkm1WbyOVrP7p0UZkC++4mUYWIduzYQb16W9DpDe/RvA/TSWFrOO09\n2Zs2bTpJDx+W0uTPeDTw/d4kEAjIxMSEtm/3oLvhA4ljZ0f7/vuPiIiSkpJIW0ubbjncokBeIP0+\n4Xdyd9egvLxg+i7yGl0IMqPQc0PoxgFTEoQnERFRZWUJHfY3ppsxBykpPowCLmtScO+jlOWbRUKB\nkKZMmUJ//PEHERGFhRFpaxM5ahbTNZVAOrrrKB09epTEYjElrEygm4Y3KWltEgmzhfTkSQr5+uTT\nQatHdIJ7i/6xfUphCxPo1spbFPJPCOX651JRZBHd9CunUaOIDA2JVq8mmvnZTWIbmtIguJEZ35m0\nFY1p7dr9tH37OVLkm1JflgupKe8hPt+cpkyZQunp6TLXv6iyksxv36arOTlkeusWPS0ultm+MTmZ\n5j99KlM26fFj2l2jnnv37pGFhQX179+fDAwMaPPmzVRa60WgJmKxmJxun6MboQMoMFCNAta/T1ev\n3iPNoCDSDAqiX85GUqBuMBWlFpGtrS1duHCBsgsLiW1oSHt9fYmIaF1SEs1+8oRKE0sp+3IOnZ6f\nTt/oJFIvpXzSWRJPFn/G0tChRGpqRI7dhMRmceji6BgK6XmX/BX8KdonntZdGkv93lOlDz5YQadP\ni6migqikhOi338SkYPsbQUeXtp7JopqPrL29PV27dovMzYlsLofQjQPmFHjehM5P/JF8PSJoj+I1\nUlc2pW+/PUvXrhGZmBCtWR9Dp7Ya0ua9o2iPchgdUwulcZa5FFtcTOp//kkAyNXFldZZfEt+fmAU\nBKMgGi0naoaCcHBwICKioKAgGjx4MJ09e5acnZ1fUcS2o+ZJ9g0Lo7tVSq2aEQ8e0JmsLAoPJzL4\nOplOe+ymG3usKDcol7Kzid4f6k/Q1KKdB7bSuXOGdP2YIZ3932HS0dGhvbus6fKgP0ll9UPi+QfR\nqTMn6ORJZ1q8eB1t9XclM3t7sre3p6+++opEIhGdutKF3vOeSx999BEREW3atIlmzZpFwmwhlcSV\nUGbmE1JVBT1/nkH3Cgqo+82z9PjxZEo9HULBusGUF5xHIfn5NOXKRho7So1M9ZTI/+d5VJ5VTkRE\nMTExxOfzqaCggHJyiMzNiY4fJ7p3j2gZL5Z2OURTWamYYhbGUGiPUMp9VkaHDxONHi3pyD74gGjN\nGqLgf/Nox/AU+kopnrbZRdP5Po/oqN49Oix3hw7J3aHNmyUdWTVXguJpvOpMcpy+hHxV/MnYQETa\n2kSrB4WRINnsAAAgAElEQVTSsD5fUa9eLqSldZn27697f5bExdEnkZFERDQlMlKm4ycimvj4Me3L\nyJAp+zctjaZFRdGJE0TffispEwgEdODAASqq9QJQHwG5udQ1JIREIiEVFj6gxNWJFD03mq4JBJRV\nXk4R7hGU8ncKERGdPn2a7O3taenSpWQ9bBitiI8nsVhMXUNCKCg3l86dI+rWjahfP6LLl4nEYqK4\nkhLSDQ6mcpGIhEKiO3eI5OQUyc2thFRViXo4iknVroQULgZRX+futHKlIR061J2mTv2XrKyKaMIE\norg4orHjxtHGjRulcj99+pQMDAxIJBLRtWtE5suD6OpVDQqes4kOXLQhfaNKOjoigX7tcZAUFQ3I\n0vI5HT4cQwu/1CBleS6NGqtK8fGnaK5lJp1WuU2iChGpOTrSIh8f2uG9gyx0eWRrq9KpFcTatWvJ\nyMiI1NTUyM7Ojq5fv06//PILTZs2jYiIEhISiMVi0d69e8nU1JT4fD79/vvv0uNLSkpoxowZpKmp\nSV27dqU//viDjI2NpdtrKgixWExr1qwhKysr0tbWpkmTJpFAIGjfE24H2kRB9OjRg4iIlixZQgcO\nHCAiop49e76KfG1KzZN0u3+fbtS6wW7379N1gYDy8ogU3bJp3sFrFBigQUREP/xANPi7HDKcMZOG\nDu1GgYGLaNaHH5IGT45OnFhPwRfN6W+7R8S57k8zoqJILBbRnTt2dPGiCn0bcI2m//cfubu7U3Fx\nMQUEEH11YBptufoD6erqUnR0NA0aNIjOnDlDSUlEISFEGRl7aNQoU/rrr7+IiKjP3bt0KSeHiIhy\nLudQsE4wnbUKooPKR4mnwqWBA1Ro2rS5lJJClJNDNHv2bPrll19IJCIaNoxo8eKX5/kiXkjn5YNp\nLesB/cO+R4Y8IamoEHl4EO3ZQ5SXV/faCQREy5cTTZhAtHkz0aMIEfkr+FNlSaXMfjmXcui06x0K\nzsujsH5h9MI3m0oFFRSgFUQ2xwOpXCSiyEgiAwOiQ4deHveosJB0goMps1yi4DanpNDc6GiZuo1u\n3qS4mtqIJB2wwc2bNGasmJSUiGrpfBKLiRYsIMrMrP+ZmBYVRRuTk6Xfy9LLKEgjiCoKKyj7fDbd\nsbtDIqGoqi4xDR48mHg8Hl2LiSHDmzfpZl4eWd+5Q48fi4nPJzp/XtJmTQbeu0enXryQfufz+fTi\nxQsqLia6eZNo5qNoWhEfTwMHDiQ/v+uUk3OFbt0aTf7+ZpSb609ERBEREWRgYEAlVee/du1amj9/\nvrTOH//vb/r90of0++NkOnjBhPbtu0VFUUV00/Am/fjjjzRoUD+yteVSXwsz8v3Rl3R0NGn3bi0S\nCNLodq8wOvHrCdK3sqIR9+/Ts1VRdOOiOl28eKjTKojo6GgyMTGhjKoXhqSkJHr27Bl5e3vXURCf\nf/45lZWV0YMHD0hBQYGiq56rJUuWkJubG+Xl5VFqaio5OjqSiYmJtI2aCmLTpk00YMAASktLI6FQ\nSPPmzSNPT892Puu2p00UxPDhw2nu3Llkbm5Oubm5VFpaSt27d391KduImic58uFDOpOVJbPdKSyM\n7lT1MOoOxWQWdIsCApSooqKQ7OyIPgmOpV+io8nOTpvc3buRkrwp7fi2BwUGqlPgN9/QB6o5tCI6\nUVpHVtYZOnBgPQ36LocG37snbWfA1EJ679xqOnP+Q/Ly8qIpU6YQj8ej0tJSWrqUyMyM6NGjKXT6\n9BLi8Xjk6upKfUePJru5c6mwsJCIiIqii2jw3ps0YdanNGjQYjI1fUIcjjlpaZ0mFZVEYrM1aebM\nHJo9m2jgQCKhUPZapO9MpwcTHlNuRiXl5BBVVdsiQrqEUOFD2QNTt6RS9GeSH2Da9jR6NPYRpW2V\n/O0XFkbXqpTyo0cSJbFgAVF2tmR0sCklRVpPWEEBdQsJoawsyWjmVlwp6QQHk7hW7ysWi8n05i1S\ntS+igQOJduyQlfHaNSKA6Oef68qfIxSSemAgZQuFJBYTVQ9OHo55SGlb0yikawhlnZV9RmJjY+nK\nlStERDQgPJzs7tyhVQmJNHQoUY0XfBl2p6eTe0SE9LuFhQU9e/aMiIiSSktJKyiIsoVC6tmzJ4WF\nhUn3y84+TzdvGlBc3BISicpp/Pjx0lFEv3796PLly9J9w+9PoRGXfyT5XWG0+sivFBk5lYiIQh1C\nKcnvBrm7K9LmTXMogBdA5ZnltGXLFnJ2NqX7990pfX8a9VLvRdv37CHL27fpyvyfKey6O4nF4qYV\nhGQ569f/tJDY2FjS1dWla9eukbDGw13fCCItLU263dnZWeqjsrS0lN5LIokPq6ERRNeuXWXMTenp\n6cTlckkkkvWTvem8ioJocsbUsWPH4OHhgStXrkBDQwO5ublYv359K7vKW5f65kIUiURQrZpYZqWi\niPRKIeQVjPH0aSoKC4H7XAFGGBjg99/tIS+vin+23IH8/v9BOe99lBx0h/N8Day0M0O/qjhzPn8U\nRo78HhFH1BBWUIRKsRghoYTwQTEwyR4FRe4dfP75HBw/fhweHh5QVFREeDhQVCTC8+dX8dFHC/Do\n0SOsXr0a8z/+GPExMeg1ejQSi4sRYyhGvNpz+Pn64tGjZfDz64KAgAPgcudh+PAfMW3aZ+jRQwss\nFnD0KFAryAwGsw3Q/UQ3aOhzoKUF1IiGbDZKdkoojZFNEVKWUAZFC0UAgO5kXeT55yF5XTKMvjbC\naD5fOrPcwQF49EjSO3SxJ5zPyMU4zZeT6bqrqCCpvBxPkitw6xYwamkBunN4MovLA5KINPtyTWh/\nmIfvvgP27JGVcdMm4LvvgK1bgdprQK1PScEYPh9hflw4OwMWFpJ01+k9DRC3OA4iDXlsCNaGgQFw\n4IDkGGtra3z44YcAgHmGhogpLYVRpB6Sk4Gvvqr/On2ip4fYkhLcrJpZraqqiqKiIgDAuuRkfGZg\nAG0uF0VFRdKIIwDQ1h6Ovn0jUFLyBBERg/HTT8uwbt06xMXFISYmBm5ubgAkc2JKi69DJP8+xGZF\nmD/mCwgE5yEUvgBvdioSyz/GgQO74Wm+FrzePMjryWPu3LkoL9fApUtJCGD/gqyiLEzsORanze3B\n6XYKpcYz8KiJFB5VjbfOp4VYW1tj06ZN8Pb2hp6eHjw9PetdFhQA9PX1pf8rKytLr316errMvBRj\nY+MG20tMTMS4ceOgqakJTU1N2NvbQ05ODs+fP2+x7G8bTSoIFRUV6OjoIDg4GAAgJycHa2vrNhfs\ndahPQRSLRFCpCnu1NmNDs1IBYjkDBAenwG1yGbIqKtBHTQ0mJgIcPboNM2ca4DZZIn/KYgTlW2Hh\n4rqXSl0dmDaGC8UieUSWlOBL30zoGxM+M+uG7GwLaGi8wBdffIE5c+aACAgLA7ZtC0dmpj7k5Ixh\namqKQYMGYc706bjv64uysjJ0mTkTEyMjoXXsGHr2nIePPuLDykqyaPu8efNw5owv/vhjMb79Ftix\nQ5KIrS1QtlVGyVPZlB5liS8VhJyaHPgT+GArsKHxvgZGaWvDNztbGk+trQ388w/wf5eLIMqSx+1z\nCtJ6uGw2+qqpIbSoAL17Az2n5iN0tzoeP64rBztCE0quuRg+HHj6FIiLk5THxgIhIcCqVUCfPsDB\nGqm1AvPysDM1E08XW+GbbyRrIeTmAtOnA16ntRBdoYqFT6wgrGBhxgzAz69uu5N1dHDIthtWf6OI\nTZvqKuFq5Nls/GRmhl8SEgAAampqKCoqQlhBAY5lZWFxVSdVWFgINTU12WPldeHgcBocjjr4/EAM\nGDAAH3/8MYYPHw75qlnfRUUPICenibG23TFCRwuaijrg8ycgJuZLZPWeC/Y/S6CrMxlZJ7Kg87FE\nCXM4HGze/Dd8fEqwdt0BfDbDEZk+mdC6FwmWWTo8s8yws4EOt7Pg6emJoKAgJCUlgcViYcmSJXVe\nIBrDwMAAKSkp0u81/6+NqakpLl26JLO8aElJSbPWuH7baVJBeHt7Y926dVizZg0AQCgUYvr06W0u\n2OvQ1AjC0hLgFSrhVqkaLvFvwm9kBIZraYEFoKwsEYqKZuBwgJ6LdMAuEYEzRLfBjnjBAqA4jIcd\nj3IQ4RSPQ0626N2Thbt3ByM3NwB///03hg4dioQEQFkZ6N37EpKSPHDokGw93dTV8ejCBVg8eQLr\n/fuRdPkKoqIWY+nSl/usWLEC4eHhMm9NbYWyXT0KosYIAgAsVlmg66GuYLFYcFBRAYfFwoOqN7hq\nErVyYVukidppq1x4PISXF0BNDSgwKcC3H/Lg7i5JTV2TmGMaSNfJA1uOMHUqsHevpPzvv4G5cwEl\nJWDxYmDjRsnLal5FBaZFPoHc/2wxeag8Hj8GJk4EFBUlCiLsPhsDwnsjKEMNGzYAn3wC3KpnmXJF\nDgcpB3XQpQvw0UeNX6uZ+vqILytDUF4eVFVVkZWXh2lPnmCztTX0pB19UR0FAUhGSTY2fyMpaTWW\nLp2PBw8eYNy4cdLtublXoan5IT43MMARe3sAgLHx18jL80O37schnzgYef55yDmXA/64lxMuBw0a\nhAEDXJGXpwP3WQnI5P6GtPh/oZE/CQtNzLG59oXuRMTExMDPzw/l5eVQUFCAoqIiOA2ks2mISZMm\nYc2aNcjLy0NaWhr++eefBhXM/Pnz4eXlheTkZABAVlYWzpypP1fbu0aTCuLUqVPw9fWVLghuZGSE\nwsLCNhfsdWhwBFFtYrICevjboKuyHbTDhTjdoxu22tqioiIHbLY85OQkqTOmLlbENjMHTN2g0WBb\nXbsC5iU8/FOciH6lunDVUYOGBpCc7Ib0dH/pfmFhQN++gEBwCf37e+D334HaGUE0NDRw8fx5RJw8\nif795qFPHz569Hi5XU5ODt26dXudS9NsGjQxmb9UEAoGClDrKen0WCwWxvH5OFVLE1zLzYV1gSZq\n5yh0UVfHI8qHkqYIkcXFWDpODbNmAStXvtwnMREoiFeAkbI87hcWYtQMIf5X+gx9Q8OxKyYLX3wh\nGa0MGQKw2cC1a8CXMbFghWpjojEf334L1O5XWCzA0VGiMACJOSw9HXUUWG4u8McfwIb6U3bJwGWz\nscLMDL8kJkJVVRVbnz1DHzU1TNHTAwCIxWKUlJRIf0O1UVa2gaHhfKio7MLJkycxYsTL5EsCwRVo\naQ0Fi8WCYtXJqKr2gIvLC2hqvg/dSbqIXRgLFQcVKBgqyNS7detWXLx4GU79g8AZfB8lXQ7A2Ppz\nfG9igp12dk2fWAdRXl6OZcuWQUdHBwYGBsjOzpa+oNbs5BsbUfz8888wNjaGhYUFhg4diokTJ0pH\nZbVZtGgRRo8ejaFDh4LH42HAgAEIDQ1t3ZN6U2nKseHk5ERELyOXioqKyNHRsUmHyKeffkq6urrS\nMNma/Pnnn8RisSinKnKHiGj16tVkbW1NdnZ2Mg66sLAwcnBwIGtra1q4cGGD7dU8lbVJSfRjXJz0\ne4VIROwbN6RO0OvXiQYPJjpxYgv9889n0v3y80Pp7t1eTZ5bbf45V0Tsg3coKadCWvbJJ1l0/TqP\nRCJJ2Q8/EK1Zk0OBgWpUWVlKrq6ykT41SU3NJHPzcgoKarEorUb583IK0gySXrOKwgoKUAqo40iu\nSXBeHjnWmOxWJhKRamAgLV8jpGXLZPfNFgpJ8XogfbRUQM5VzluBgIjPJ6qeDuHjQzR9OtGCmBjq\nffcuaQYFEX9lDPVZ/Jx4J0PIPSKCHhQWUnxJCX13UEBWv8cT/1wIuQ6prOO4bwx3d6KqOYVSDhyQ\nhAU3lwqRiKxu3ybH8eNJ66efKLeGAPn5+aSiotLo8ZWVxXTrlhkJBNdrlJVQYKAqVVTkN3hcUVQR\n3cANStmU0uA+RES5d1MpaMJKEle+vH/N+Pm/Nfj4+JCbm1tHi9GhNHS/G3sOmhxBTJw4EfPmzUNe\nXh62bduGIUOG4LPPPmtS8Xz66ae4dOlSnfKUlBRcvXoVZmZm0rKoqCgcPXoUUVFRuHTpEr788kup\nLfuLL77Azp07ERsbi9jY2HrrrE3tEUSxWAwVDkf6xmFpCTx7Bty8aQJLy1TpfhLzknmT9dfmqxEq\nyBzqDFOtl5lLunblo7jYFEVF9wBIRhC9e5+FuvpAcDiK+Okn4M8/668vIEAPxsbyeO+9FovSanB1\nuAABFdkVAF6OHhp7axvA4+GFUChd/+J2fj7slZWhq8xF7UGnNpcLnlAB8fbpcKlKdqipKXE6r1gh\n2efCBWD4cGC2vj5GamvjibMzfuLZIPwvXVww7ItR2toY8uABBkVEINQuEWnl5eCs7IaTBzkN+gzq\nlXsAcPu2bNn588CIEfXvXx9ybDZWmJvjkViMqWpq0KghQEPmpZpwOMqwtt6E2NivkJ9/GyJRGfLz\ng6Cq2hNycrwGj1PpqgKDeQbQmdR4Rl2NvkZwObQcLE7z7fhvMpmZmbh58ybEYjGePn2Kv/76S8Z0\nx9A8mszm+sMPP+DKlStQU1NDTEwMVq1aJY30aIyBAwcisZ4FdRYvXox169ZhzJgx0jJfX194enqC\ny+XC3Nwc1tbWCAkJgZmZGQoLC+Hs7AwAmDFjBk6fPg0PD49G266jIGqYlwDA2Bh48QK4ds0EEye+\ndF69qoIAAB2+7A+vZ08gOnowevQIgKqqM5KSkqGsvASmpicASMwiEyYABQUAr9bvf+9eYNGiVxKj\n1WCxWFCylZiZ5HXk6/gf6oPNYmEMn49TWVn43tQU1/PyMERTE2pqqKMgAMA4j4f7Rplw4dlLyxYu\nBGxsgJs3gYAAybXQUlNDr6oOdvp0IC8PcO3PhiuMsbBGdMqZNMB0HFBl2Wk2Li4Sc1I1lZXA5cvA\nunUtq2eanh78zM1hKBbLlBcWFspEMDUEnz8GRUURiI39CiUlT8HhqMHI6Msmj7Pb2jxzEVv+rVv+\npUGEQiHmz5+PhIQEaGhowNPTE19+2fS1ZJClWem+hw4din79+qGyshIsFgsCgUC6zkJL8PX1hbGx\nMbp37y5Tnp6ejv79+0u/GxsbIy0tDVwuVyY8zcjICGnNcK7VVhA1HdQAICcHmJgA+vrGqKyUVRDK\nyq2TyrxXL+Dff90wdOhulJYugpfXJJiafgcNDcmwgMuVKJGwMOCDD14eJxZLonOqQy87kmpHtbqr\nerMUBACM4/OxKilJoiByc7HKwgK5DSgI3Sx1kH4mBtTQkMrKkhHExIlA9+5A7cdMSwv45Zf62x49\nuiVn95L+/SX3obJS8mzcuSN5PhqJjKwXDosFWz6/jo+uvgim+mCxWLCw8IaFhTdEomIUFt6HiopD\ny4RgACCJTHr06FFHi/HG0+Qrxb///gt9fX10794dffv2RZ8+fdC3b98WN1RSUoLVq1fj119/lZbR\nK8RINwe1+kYQtdZcsLICPvxQE0SVqKyUeFBfZwRRG0ND4MmTQcjLC0Zc3GKwWHowMfleZp9+/STK\noCZRUYCOjuTT0dSMZCpNKIWShVKTx7yvqYmokhLElJTgYVERXHi8BkcQWinqMChTgbGirOKZMwdQ\nUQGGDWuV02gSDQ3AzAx4+FDyvaXmpZrUnAdRTXNMTLXhcFSgofEeuNyGAyQYGNqaJkcQ69evx+PH\nj8GvsWbBq/Ds2TMkJiaiR1VYTmpqKvr06YOQkBAYGRnJxCmnpqbC2NgYRkZGSE1NlSk3MjKqU3c1\n3t7eACSrsKVaWqI6BKj2CAKQxOgbGLAQGWmC8vJUyMnZt6qCYLEAS0tdVFQYA7iAnJzwOvb7fv2A\nw4dlj7t1S2Ly6Awo2SrhxaEXACRzIDQGNd1ZKbDZ8NDSwnfPnqE/jwclDkcSylrPSqvsDGWsee5U\np5zLlUQktaeSHDBAcu1795YoiK1bX62e+hREc01MDAztgb+/P/z9/Zu1b5MKwtLSUrqgzuvg6Ogo\nMzPRwsIC4eHh0NLSwujRo/HJJ59g8eLFSEtLQ2xsLJydncFiscDj8RASEgJnZ2fs378fCxcubLCN\nagXxsKgId588kZbX9kEAEjs3ACgoGKO8PAXKyl2lcyBai169gKdPf8eNG9aYN0+zzvZ+/YBvvpHE\n71frjtu3JZ1VZ6DmCKK5JiZAYmaaHBWF1VWLIfN49Y8gCguBhl6szVrvNjQLFxfg6lWJmSo9XXJv\nXgU1NbVXNjExMLQHbm5u0pn6AGSsOrVpUkGsXbsWAwYMwIABA6RxxCwWC5s3b270OE9PTwQEBCAn\nJwcmJiZYuXIlPv30U+n2mm/T9vb2mDRpknSKu4+Pj3S7j48PZs2ahdLSUgwfPrxJBzVQvw+itoKo\nRlFRMoKoqMgCm63YaMRIS+nVCzhyZCz8/IBt2+puNzOT+BxSUgBTU0nZrVvAt9+2mgivhZKNEkrj\nSyGuFNeZA9EYw7S0oMBiYYimRCk2ZGIqKmpYQbQ3Li6SORjnzwMeHnXnTzSX1jIxMTB0BppUEJ9/\n/jnc3d3h6OgINpsNImrWlPfDtW0ntYiPj5f57uXlBS8vrzr79enTp8XOpvrCXGubmKpRUDBGWVlK\nq5qXqunVC/j0U8DISBLCWRsW66UfwtRUMlkrMxNop7lwTcJR4kBeTx5F94oANsDVbF7sqJqcHEL7\n9IFj1cSwhhREYyOI9sbWVmIG27lTEmr7qlSn2qgJY2JieFNpUkGIRCL89ddf7SFLq9FUmGtNFBRM\nUFAQUqUgLFpVDmtryQzfxnz61Qpi4kRJ9Iyz86u/vbYFynbKEFwWNMtBXZPuNTrEagVR05QGdC4F\nwWJJTHsXLzadWqMxVFVVGRPTW8CePXuwc+dOBAUFtei4oKAgzJ07F9HR0a8tw6xZs2BiYoJVq1a9\ndl2vSpNRTMOGDcO///6LjIwMCAQC6aczo8Rmo1wshqgqSqo+J3U1CgoSE1NbjCA4HImfvDkKAuhc\n/odqlO2UIbgkaLb/oT64XEn4aO2Mq4WFr5Zptq1wcZF8XiGCWwpjYnq3GThwYKsoB0Bihm9JgsK2\noMkRxKFDh8BisbB27VqZ8oSq7JWdERaLBRUOB8UiEXhycvWGuVZT7aSWzIGwr3ef12HlSqCxtDdO\nTsD9+0BFhcT/sGRJq4vwWijZKiHNJw3G37RwUkAtqiOZasY7dKYRBAB8/jkwduzr1dGQk9rKyur1\nKmZ4J2mrqQDNpckRRGJiIhISEup8Ojs1zUxNjyBSUFaW0OojCABwd5dMumoIdXWJ/yEiQjJZ61Wj\nZ9oKZTtlQIzXGkEAdSOZiDqXkxoA+HzA/jXfERoKc2VGEC0jJSUF48ePh66uLvh8Pr7++mt4e3vL\nZJJOTEwEm82GuGrmupubG1asWAFXV1eoqalh9OjRyM7OxtSpU6Gurg5nZ2ckJSXVe2z18Tt37myW\nfBcuXEC3bt3A4/FgbGyMDVVZHf39/WXWoTA3N8eGDRvQo0cPaGhoYMqUKSgvL5duX7duHQwNDWFs\nbIwdO3aAzWbX8c9Wc+7cOfTs2ROamppwdXVtl4mAzZp7//jxYxw7dgz79u2Tfjo7NRVEYz6I6syt\nRUUP2kRBNId+/SRrO5ia1u/M7kiU7ZQBoMU+iNrUdlSXlUnMTi3JmfQmoKysjNLSUpmOhzExtQyR\nSISRI0fCwsICSUlJSE9Px5QpU5plbjl69CgOHDiAtLQ0PHv2DAMGDMCcOXMgEAjQtWvXRkM6W2LS\nmTNnDrZt24aCggJERkbig5rpEGrVefz4cVy+fBkJCQl4+PAh9lStfHXp0iVs3LgR169fR2xsbKNz\nE+7fv485c+Zg+/btEAgEmDdvHkaPHg2hUNgseV+VJk1M3t7eCAgIQGRkJEaMGIGLFy/ivffew4wZ\nM9pUsNdFRkFUJeurDxaLBQUFY5SURLfqHIiW0K+fJLR12rQOab5RFEwUwFZkNzvEtSFqK4jOZl5q\nLdhsNpSVlVFcXCxVCm9qFBOrmZOpmoJqxNw3h9DQUGRkZGD9+vVgV5mGXV1dcfXq1UaPY7FY+PTT\nT2FRNf9m2LBhePLkibTznjhxIlZUZ4J8TeTl5REZGQlHR0eoq6ujV69eDe67cOFC6Rouo0aNQkRE\nBADJap2zZ89G165dAUjmIxyqtVBMtcLatm0b5s2bBycnycTSGTNmYPXq1bhz5w4GDRrUKudUH00q\niBMnTuDBgwfo3bs3du/ejefPn2Pq1KltJlBrodZMExMgMTMJhVmQk+uYHsvZWfJG3dkc1ADAYrPg\ncNoByl2VX6ued0VBAC/NTNUK4k0dQbS0Y28tUlJSYGZmJlUOLUGvRqZGRUVF6Orqynyvbf5rDqtX\nr5auRzF9+nT4+Pjg5MmT+O2337B06VJ0794da9eulcknV5OaC3wpKSlJl0/NyMiQJiIFGl8WNSkp\nCfv27cPff/8tLauoqGhwKdbWosk7oKSkBA6HAzk5OeTn50NXV7fR5fs6C6ocDgqbYWICJApCSal1\nQ1xbgqOjJPdQZ0mxURutj7TAYr9eNEV9CuINfKluFrX9EG/qCKKjMDExQXJyMkS1VtRSVVVFScnL\nVQ4zMzMbracxc1H14k3Nqc/LywuFhYUoLCyEj48PAKBv3744ffo0srKyMHbsWEyaNKnxk6qHli6L\nunz5cpllUYuKijB58uQWt9sSmlQQTk5OyM3Nxdy5c9G3b1/06tULLp21J6tBc53UgCSSqaP8D4DE\nDh8ZCXRpnUSynZLa+Zje5hFE7UgmxkndMvr16wcDAwMsXboUJSUlKCsrw61bt9CzZ08EBgYiJSUF\n+fn50rf6mtSM+mksAkhHRwdGRkbYv38/RCIRdu3ahWfPnjVLvoqKChw8eBD5+fngcDhQU1Nr0ZKo\n1XJNmjQJu3fvRnR0NEpKSurMdyAi6b5z587F1q1bERoaCiJCcXExzp8//0ojopbQqIIgIixduhSa\nmpqYP38+rly5gr1792L37t1tKlRrUMdJ3chwVVt7BPT0OtYB0N65h9qb2lFMnS2CqTWpPYJ4U01M\nHd9qN8cAACAASURBVAWbzcbZs2cRFxcHU1NTmJiY4NixY3B3d8fkyZPRvXt3ODk5YdSoUXVGCbWX\nJG1s+/bt27F+/Xrw+XxERUXB1dW10WNrcuDAAVhYWEBdXR3btm3DwYMH622jNjXr9fDwwMKFC/H+\n++/D1tYWA6pszAoKCnX27dOnD7Zv344FCxZAS0sLNjY27RIsxKJG1CwRwdHREY8fP25zQV4XFosl\n88awKDYWlkpKWGRsDKs7d3Cpe3fYKL+eHZ3h1fnlF8ls5ap8ijh2DDh+XPJ52xgxYgS+/PJLjBgx\nAkQEOTk5lJeXQ06uWcuvtBu1fzMMHcuTJ0/g6OgIoVD4Sv6Xpmjofjf2HDQqBYvFQp8+fd7IBbxr\njyAaMzExtD3vopMakNi45eXlO51yYOgcnDp1CuXl5cjNzcWSJUswevToNlEOr0qTkty5cwcDBgyA\npaUlHB0d4ejoWGdFuM5Ic8NcGdqHd9VJzZiXGBpj27Zt0NPTg7W1NbhcLrZs2dLRIsnQ4GtNwv+z\nd99hUVxdHIB/Swcp0pUmKCgi2LBiIyJEoxArgsagmJhobIklRk3ERAVbosaQLyq2GEEsEY2KHbti\niRUFRDqISAdpu3u+PyasrOzSYRHu+zw+srMzc8/M7s6Ze2fm3thYWFhY4MyZM+9lNVRdXh4pJSXc\nBZ0q7mJiGl5LqkGUv0jN7mBiKnPq1ClZh1ApqQli/PjxuHv3Lry9vXH+/PnGjKlelNUgCoVCKMvJ\nQV7GnV61dO/exZSf3/SeGq8v5WsQ7A4m5n0mNUEIBAKsXr0akZGR+Pnnn8VqETweD998802jBFhb\nZQmiqltcmcbx7l1MeXlvB0lqbtTV1ZGdnQ2ANTEx7zep1yCCgoIgLy8PgUCAvLw85Ofni/6921tl\nU1SWIKq6xZVpHKyJiWHeP1JrENbW1qLHyD/66KPGjKleaMjLI4/Pr3S4UabxtNSL1KyJiXmfVXlq\n/T4mB0C8BsGamGSvJdUgyo8qx5qYmPdZs217ESUIdotrk/BugmjOT1KXH5eaNTHJVmXjK9TEzJkz\nsWrVqnqIqP5iagzN9ukddpG6aVFTA4qLAT6fGweiudcgWBNT43N0dMSUKVMwffr0el93U3s+obFU\nmiCys7MRGhqK5ORkAFx3tB9++CFat27dKMHVhdhFapYgZI7He1uL0NZu/gmifBOTdnO9n7eJkfX4\nzc2R1CamvXv3wt7eHmFhYSgsLERhYSEuXLiAnj17Ys+ePY0ZY62oycujUChEHruLqcko38zUnC9S\nsyamujE3N4efnx+6dOkCHR0deHt7i7qjGDVqFAwMDKCjowNXV1fRyeuyZctw5coVzJ49GxoaGpg7\nd65ofWfPnkXHjh2hra2N2bNnV1r2119/DUNDQ2hpaaFr166IiIgAAEydOlU02FBYWBhMTEzw888/\nw9DQEEZGRqJR4gAgIyMDrq6uomFOly9fjkGDBkksr7i4GAsXLkS7du3Qpk0bzJw5E0VFRXXZffWL\npLCysqKsrKwK0zMzM8nS0lLaYiLTpk0jAwMDsrW1FU1buHAhWVtbU9euXWnMmDGUnZ0tem/NmjVk\naWlJnTp1otOnT4um37lzh2xtbcnS0pLmzp0rtTxJm9Lq0iX6MTaW5kVFVRkv0/A6dyZ6/JhIKCSS\nkyMqKZF1RA3j1atXpKenR0REU6ZMod27d8s4Iskq+fnLVLt27cjOzo6SkpIoMzOTBgwYQMuXL6eM\njAw6cuQIFRYWUl5eHk2YMIFGjx4tWs7R0ZECAgLE1sXj8cjV1ZVycnIoISGB9PX1KTQ0VGK5oaGh\nZG9vTzk5OURE9OzZM0pNTSUioqlTp9L3339PREQXL14kBQUFWrFiBfH5fDp58iSpqamJjmcTJ04k\nT09PKiwspIiICDI1NaVBgwaJxRQTE0NERPPnz6ePP/6YsrKyKC8vj1xdXem7776rpz0pTtrnXdn3\noMan1tWtxk2bNg2hoaFi01xcXPDkyRM8ePAAHTt2FPXnHhERgQMHDiAiIgKhoaGYNWuW6MG8mTNn\nIiAgANHR0YiOjq6wzsqoy8vjZUkJa2JqIspqEEVF3BgYzW086jLvPgfxvl6DCOOF1cu/muLxeJg9\nezaMjY2hra2NZcuWITAwEDo6OhgzZgxUVFSgrq6OpUuX4tKlS2LLkoRugZYsWQJNTU2Ymprigw8+\nEA35+S4lJSXk5eXh6dOnEAqF6NSpk9hocOXXraioiB9++AHy8vIYMWIE1NXVERkZCYFAgCNHjmDl\nypVQUVFB586d4eXlJTEuIsL27dvx888/o3Xr1lBXV8d3332HoKCgGu+zhiL1GsSyZctgb28PFxcX\n0VB4iYmJOHPmTLXGdR00aBDi4uLEpjk7O4v+7tu3Lw4fPgwACAkJgaenJxQVFWFubg5LS0vcunUL\n7dq1Q15enmhYvk8//RRHjx7F8OHDq7Vx6vLySCspgcl//aszslWWIJrz9QeA68+fz+ejtLT0vW5i\nciRHmZVtamoq+tvMzAwpKSkoLCzE/Pnzcfr0aWRlZQHgrvEQkejEVdIJbPmDfNl44QDQpUsXJCQk\nAABCQ0PxwQcfYPbs2fjqq68QHx+PsWPHYsOGDRITvK6urlivq2pqasjPz0d6ejr4fL5Y/NKGEk1P\nT8ebN29gb28vmkZEEAqFVe+gRiK1BuHl5YXbt29j8ODBUFFRgYqKChwdHXHnzh1MmzatzgXv3LlT\n9IxFSkqK2E40MTFBcnJyhenGxsaiNsfqUJeXR1ppKatBNBFl/TE19wTB4/FEdzKx5yBqp+zAXfa3\nkZERNm7ciKioKISHhyMnJweXLl0SG3Wtuq0bZfM/efJENJRo2WBBc+bMwZ07dxAREYGoqCisX79e\ntFx11q+vrw8FBYVqDSWqp6cHVVVVREREiIYRzc7ORm75TstkrNK7mHR0dODp6YmMjAwAXNasD6tX\nr4aSkhImTZpUL+sr41M2Gg24W97UNTXxsqSE3ebaRJT1x9ScL1CXKbtQ/T7XIGSFiODv749Ro0ZB\nVVUVq1evhoeHB/Ly8qCqqgotLS1kZmZi5cqVYssZGhpWOWyopKaeMnfu3IFAIEDPnj2hpqYGFRUV\n0VCi5RNRZeTl5TF27Fj4+Phgx44diI+Px59//ol2EoaMlJOTw+eff4758+dj69at0NfXR3JyMp48\neQIXF5cqy6qtsLAwhIWFVWteqTWI+Ph4eHh4QF9fH3379kXfvn2hr68PDw+PCk1HNbF7926cPHlS\nbIg+Y2NjsSyblJQEExMTGBsbIykpSWy6sbGx1HX7+PiI/jk6OrJrEE1MS2liAt4+C/E+X4OQFR6P\nh0mTJsHFxQUdOnSAlZUVli9fjvnz56OwsBB6enpwcHDAiBEjxM7q582bh0OHDkFHRwfz58+Xum5p\nNYHc3FzMmDEDOjo6MDc3h56eHhYtWiRxucpqE1u3bkVOTg7atGkDLy8veHp6QklJSeKya9euhaWl\nJfr16wctLS04OzsjKiqqejuqlhwdHcWOlZWSdvW6b9++FBQURKWlpaJppaWlFBgYSH379q3WVfPY\n2Fixu5hOnTpFNjY2lJ6eLjbfkydPqFu3blRcXEwvXryg9u3bk1AoJCKiPn360M2bN0koFNKIESPo\n1KlTEsuStCnjHz8mXLxIx98pj5GNJUuIVq8mOnmS6MMPZR1Nw+rVqxfdunWLtLW16fXr17IOR6JK\nfv4yZW5uTufPn5d1GPVm8eLFNHXqVFmHUb93MWVkZGDixIliQyUqKCjAw8ND1ORUGU9PTzg4OCAy\nMhKmpqbYuXMn5syZg/z8fDg7O6NHjx6YNWsWAMDGxgbu7u6wsbHBiBEj4O/vL8qy/v7++Oyzz2Bl\nZQVLS8tqX6AGIGpaYk1MTUNLqkGU3cnEmphansjISDx8+BBEhPDwcOzcuRNjxoyRdVi1IvUaRM+e\nPTFr1ix4eXmJrsgnJCRgz5496NGjR5UrDgwMrDDN29tb6vxLly7F0qVLK0y3t7fHo0ePqixPkrLE\nwJqYmgYNDSAlpWUkCHV1dWRkZIDH40GZ3UXXouTl5cHT0xMpKSkwNDTEwoUL4ebmJuuwakVqgti7\ndy8CAgKwYsUK0Z1DxsbGcHNza5C+ThoCq0E0LeXvYmruJ9Xq6upITU1l1x9qITY2VtYh1EmvXr0Q\nHR0t6zDqhdQEoaysjFmzZomagd5HrAbRtJS/i6m5Hzc1NDSQmprKmpeY91qtOin68ccf6zuOBsES\nRNNSdg2iOXf1XYbVIJjmoFYJYvv27fUdR4NgTUxNS0u7SM0SBPO+k9rEVNkXu7CwsEGCqW/q8vKQ\nB6DEugFuElpSgiirQZTv5oFh3jdSaxDa2tqIjo4W3apX/l/btm0bM8ZaU5eXh7q8POsnvokonyCa\ne9M8a2JimgOpCWLKlCli/aGU5+np2WAB1Sd1eXl2/aEJaSl9MQFcDTwjI4MlCBmr6/Cejo6OCAgI\nqHMcPj4+mDJlitT3zc3Ncf78+TqXU9+kJojVq1eLelF917p16xosoPrEEkTToqHBXaBuCQmi7O4l\ndhdT46mvg3l5lXXNUdP1NEY59U1qgqhO1q2qYyxZs23VClssLWUdBvMfBQVAWRl49arlJAhWg2g8\nTfEAW4aq0dFfUyQ1QXz33XcYNWoUtm3bhnv37iE1NRUpKSm4e/cu/vjjD4wcORLLli1rzFhrTFlO\nDsPrqQdapn6UPU3d3I+bZYmBJYiak+WQo2fPnoW1tTVat26NOXPmiPXiSkRYtWoVzM3NYWhoCC8v\nL1HX3GFhYWJjQJRtx4ULFwBwyauoqAgeHh7Q1NSEvb09Hj58KDEGIoKfnx8sLS2hp6eHiRMnisa/\naGxSE8SBAwewadMmvHr1CsuWLYOTkxOGDRuG5cuX4/Xr1/j111+b1MhHzPtBQwMoLW0ZF6nL/8/U\nzP79+3HmzBnExMQgKioKq1atAhFh+vTpSEhIQEJCAlRVVUUH/NWrV2PQoEH47bffkJeXhy1btojW\ndeLECdy5cwcPHz5EcHAwTp8+LbHM169fY9y4cVizZg0yMjLQoUMHXLt2TVQz2bVrF/bs2YOwsDC8\nePEC+fn5lSac8jUaIkJISAjc3d2RlZWFSZMmYfTo0RAIBBWW27JlC44dO4bLly8jNTUV2tra+Oqr\nr2q1H+uq0vEgLC0tsXz58saKhWkByk6om/uJdXNoYgoLq58mG0fHmjWvlB9yFOBqB3PmzMFPP/0k\n1und0qVLMXToULFlJTXllA05qqmpKRpy9MMPP6ww38mTJ2Fra4uxY8cCAObPn4+NGzeK3v/rr7+w\nYMECmJubAwB8fX1ha2uL3bt3V2u7evXqJVr3N998g40bN+LmzZuiwYrK/PHHH9i6dSuMjIwAACtW\nrEC7du2wb98+sVHsGkOlCYJh6puGBncdormOR12mOTQx1fTAXp8ac8hRHo+HkydPIjU1tcLwoOXj\nSE1NFRv4x8zMDHw+H2lpadXapvLr5vF4MDExQUpKSoX54uLiMGbMGLFkoKCggLS0tEZ/xIAlCKZR\naWo2/9oDwJqY6qqqIUcNDAxw//599OzZU5QgajPkaHkvXrwQG7iMiMReGxkZiQ2WlpCQAAUFBRga\nGiIpKQlv3rwRvScQCJCeni62/vLrEgqFSEpKEtUSyjMzM8OuXbvQv3//am1PQ2rc+grT4mlotIwE\noaioCGVl5fe6BiEr9N+Qo8nJycjMzGy0IUdHjhyJJ0+e4O+//wafz8eWLVvw8uVL0fuenp745Zdf\nEBcXh/z8fCxduhQeHh6Qk5NDx44dUVRUhJMnT6K0tBSrVq1CcXGx2Prv3r0rWvemTZugoqKCfv36\nVYjjyy+/xNKlS0VJMj09HceOHatyvzUEqQkiLi4O2dnZotcXLlzA3Llz8fPPP6OkpKRRgmOaHw2N\n5n+Buoy6ujqrQdSCrIYc1dXVxcGDB7FkyRLo6enh+fPnGDhwoOh9b29vTJkyBYMHD0b79u2hpqaG\nX3/9FQCgpaUlGtzMxMQE6urqYs1TPB4Po0ePxoEDB6Cjo4O//voLR44cEY15Xd68efPg5uYGFxcX\naGpqon///ggPD6/VvqwrHklJqX369MHRo0dhZGSE+/fvw8nJCUuXLsWDBw+gpKSEHTt2NHasleLx\neO/tvcYtyYIFwM2bwLVrso6k4fXo0QMnTpyQ2IzQFDTV34yFhQUCAgIqXIBm6kba513Z90DqNYii\noiLRF3vfvn2YPn06FixYAKFQiG7dutVTyExL01KamADg33//lXUIDFMnUpuYymeU8+fPi7J5Y99m\nxTQvLSlBMMz7TmoN4oMPPsCECRPQtm1bZGdnixJESkoKG2OXqbW2bQFDQ1lHwTRl7/uQo82J1GsQ\nQqEQBw4cwMuXL+Hu7i56aOXff//Fq1evJD5oIktNtT2VEUcECIUA60NR9thvpmWp12sQPB4PKioq\n4PP5ePz4sShB9OjRo57CZVoiHo8lB4Z5X0itQcycORMRERFwcHDA+fPnMWrUKPzwww+NHV+1sbMh\nhqkZ9ptpWWpTg5B6xfny5cu4cOECfH19ERYWhqNHj9YoGG9vbxgaGsLOzk40LTMzE87OzujYsSNc\nXFzEnrPw9fWFlZUVrK2tcebMGdH0u3fvws7ODlZWVpg3b16NYmAYhmFqT2qCUFJSEj3EoaamVuMz\njWnTpiE0NFRsmp+fH5ydnREVFQUnJyf4+fkBACIiInDgwAFEREQgNDQUs2bNEpU3c+ZMBAQEIDo6\nGtHR0RXWyTAMwzQMqQni2bNnsLOzE/2LjIwU/d21a9cqVzxo0CBoa2uLTTt27Bi8vLwAAF5eXqJa\nSUhICDw9PaGoqAhzc3NYWlri1q1bSE1NRV5enmhku08//bTGNRmGYZia2r17NwYNGtRg80sTFxcH\nOTk5CIVCie9XNXRpfZN6kfrp06f1XlhaWhoM/7vH0dDQUNQLYkpKilifJCYmJkhOToaioqJYD4jG\nxsaiAUIYhmFamsYeNU9qgnj58qXEjqTqS0OMwerj4yP629HREY6OjvW6foZhGFmqj5sKwsLCEBYW\nVq15pTYxzZw5U/R3fXU7a2hoKOodMTU1FQYGBgC4mkH5rnCTkpJgYmICY2NjJCUliU0vu91WEh8f\nH9E/lhwY5v2VmJiIsWPHwsDAAHp6epgzZ06F5pV3m2McHR3x/fffY8CAAdDQ0ICbmxtev36NyZMn\nQ0tLC3369EF8fLzEZcuWDwgIqFZ8GRkZcHNzg5aWFvr27VuhF9nr16+jd+/eaN26Nfr06YMbN26I\n3jM3N8f58+dFryU1GwUEBMDY2FjUzbk0N2/ehIODA7S1tdG9e3dcunSpytgdHR3FjpWVqVa/GUVF\nRdWZrUpubm7Ys2cPAGDPnj0YPXq0aHpQUBBKSkoQGxuL6Oho9OnTB23atIGmpiZu3boFIsKff/4p\nWoZhmOZJIBBg1KhRsLCwQHx8PFJSUuDh4VGtFocDBw5g3759SE5ORkxMDPr374/p06cjMzMTnTt3\nrtBFeHk1adX46quvoKamhpcvX2Lnzp3YtWuXaNnMzEyMHDkS8+fPR2ZmJr755huMHDlSNMjRu+VI\nKjMsLAzPnz/HmTNnsHbtWrGEUiY5OVn0+EFWVhY2bNiAcePG4fXr19XahuqQmiAEAgEyMzORkZEh\n+rv8v6p4enrCwcEBkZGRMDU1xa5du7BkyRLRAOIXLlzAkiVLAAA2NjZwd3eHjY0NRowYAX9/f9FO\nK+tC18rKCpaWlhg+fHg9bTrDMJUpO5DV9V9NhYeHIzU1FevXr4eqqiqUlJQwYMCAKptXeDwepk2b\nBgsLC2hqamLEiBHo2LEjhg4dCnl5eUyYMKFeOlAUCAQ4cuQIfvzxR6iqqqJLly7w8vISxXfixAl0\n6tQJkydPhpycHDw8PGBtbY3jx49LXJ+k7VqxYgVUVVVha2uLadOmITAwsMI8+/btw0cffSQ6Jg4b\nNgy9evXCyZMn67yNZaReg8jNzYW9vT0AbgPK/ga4D+LFixeVrljSBgHAuXPnJE5funQpli5dWmG6\nvb09Hj16VGlZDMPUP1k9RJeYmIh27drVqmNQw3IdfamoqIiascte5+fn13ida9asga+vLwBgypQp\nWLFiBfh8foVhUcukpKSIvQaAdu3a1egGm3fXLekYGB8fj4MHD4olHj6fX6/dpEtNEOWH1mMYhmks\npqamSEhIgEAgEBtQR11dXWxYz/KjvUlSWe2lVatWAIA3b96IBnWStr53T14FAgEUFBSQkJCATp06\nARAfItXY2BhHjhwRW0d8fDxGjBghKrtsXGxp5b67bknXXs3MzDBlyhRs27ZN6nbWFeu7m2GYJqVv\n375o27YtlixZgjdv3qCoqAjXr19H9+7dcfnyZSQmJiInJ0d0Vl9e+VpPZTUgfX19GBsb488//4RA\nIMDOnTurHK60jLy8PMaOHQsfHx8UFhYiIiICe/bsESWkESNGICoqCoGBgeDz+Thw4ACePXuGUaNG\nAQC6d++OoKAg8Pl83LlzB4cPH66QzFatWoXCwkI8efIEu3fvxsSJEyvE8cknn+D48eM4c+YMBAIB\nioqKEBYWVq+PArAEwTBMkyInJ4fjx4/j+fPnMDMzg6mpKYKDgzFs2DBMnDgRXbt2Re/eveHq6lrh\nwPruxd/K3t++fTvWr18PPT09REREYMCAAZUuW97WrVuRn5+PNm3awNvbG97e3qL3dHV18c8//2Dj\nxo3Q09PDhg0b8M8//0BHRwcA8NNPPyEmJgba2trw8fHB5MmTK8Q4ZMgQWFpaYtiwYVi0aBGGDRtW\nIS4TExOEhIRgzZo1MDAwgJmZGTZu3Cj1IbvakNpZ3/uGdTzGMDXDfjMtS7121lfelStXsGvXLgBA\neno6G9CDYRimBaiyBuHj44O7d+8iMjISUVFRSE5Ohru7O641sVHn2dkQw9QM+820LA1Sg/j7778R\nEhIiuupvbGyMvLy8OobKMAzDNHVVJghlZWWx+5HL357FMAzDNF9VJogJEybgiy++QHZ2NrZt2wYn\nJyd89tlnjREbwzAMI0PVuovpzJkzolHePvzwQzg7Ozd4YDXF2lMZpmbYb6Zlqc01CHabK8O0UDo6\nOqIO5JjmT1tbW2I/enVKEBoaGhWmaWlpoXfv3ti4cSPat29fy3DrF0sQDMMwNVfZsVNqX0xl5s2b\nB1NTU3h6egIAgoKCEBMTgx49esDb27vaA08wDMMw75cqaxBdu3bFw4cPxaZ1794d9+/fR7du3fDg\nwYMGDbC6WA2CYRim5ur0HISamhoOHDgAoVAIoVCI4OBgqKioiFbMMAzDNE9V1iBiYmIwb9483Lx5\nEwDQr18/bNq0CcbGxrh79y4GDhzYKIFWhdUgGIZhao7dxcQwDMNIVKeL1IWFhQgICEBERITY2NQ7\nd+6svwgZhmGYJqfKaxBTpkxBWloaQkNDMWTIECQmJopGYGIYhmGaryqbmMruWCq7m6m0tBQDBw7E\nrVu3GivGamFNTAzDMDVXp7uYlJSUAHAPxz169AjZ2dlIT0+v3wgZhmGYJqfKaxAzZsxAZmYmVq1a\nBTc3N+Tn5+Onn35qjNgYhmEYGao0QQiFQmhoaEBHRwdDhgxhI8kxDMO0IJU2McnJyWHdunX1Xqiv\nry+6dOkCOzs7TJo0CcXFxcjMzISzszM6duwIFxcXZGdni81vZWUFa2trUa+yDMMwTMOq8iL1kiVL\noKenh4kTJ4pGlQO4niBrIy4uDkOHDsXTp0+hrKyMiRMn4qOPPsKTJ0+gp6eHxYsXY+3atcjKyoKf\nnx8iIiIwadIk3L59G8nJyRg2bBiioqLEBjEC2EVqhmGY2qjTcxBBQUHg8Xj47bffxKbXtrlJU1MT\nioqKePPmDeTl5fHmzRsYGRnB19cXly5dAgB4eXnB0dERfn5+CAkJgaenJxQVFWFubg5LS0uEh4ej\nX79+tSqfYRiGqZ4qE0RcXFy9Fqijo4MFCxbAzMwMqqqqogGI0tLSYGhoCAAwNDREWloaACAlJUUs\nGZiYmCA5ObleY2IYhmEqqjJBFBQU4Oeff0ZCQgK2b9+O6OhoREZGYtSoUbUqMCYmBps2bUJcXBy0\ntLQwYcIE7Nu3T2weHo9XaUeA0t7z8fER/e3o6AhHR8daxcgwDNNchYWFVXuYhioTxLRp02Bvb4/r\n168DAIyMjDB+/PhaJ4g7d+7AwcEBurq6AICxY8fixo0baNOmDV6+fIk2bdogNTUVBgYGAABjY2Mk\nJiaKlk9KSoKxsbHEdZdPEAzDMExF7548r1y5Uuq8VT4oFxMTg2+//Vb0wFz5C9W1YW1tjZs3b6Kw\nsBBEhHPnzsHGxgaurq7Ys2cPAGDPnj0YPXo0AMDNzQ1BQUEoKSlBbGwsoqOj0adPnzrFwDAMw1St\nyhqEsrIyCgsLRa9jYmKgrKxc6wK7deuGTz/9FL169YKcnBx69uyJGTNmIC8vD+7u7ggICIC5uTmC\ng4MBADY2NnB3d4eNjQ0UFBTg7+/PxqFgGIZpBFXe5nrmzBmsXr0aERERcHZ2xrVr17B792588MEH\njRVjtbDbXBmGYWquzuNBvH79WjRgUN++faGvr1+/EdYDliAYhmFqrk7PQbi6usLT0xMff/xxna8/\nMAzDMO+PKi9SL1iwAFeuXIGNjQ3Gjx+PQ4cOiQ0cxDAMwzRP1R5ylM/n4+LFi9i+fTtCQ0ORm5vb\n0LHVCGtiYhiGqbk6NTEB3LCjx44dQ3BwMO7duwcvL696DZBhGIZpeqqsQbi7u+PWrVsYPnw4PDw8\nMGTIkAod5TUFrAbBMAxTc3W6iyk0NBTOzs6Ql5cHAFy5cgVBQUEVOu+TNZYgGIZhaq5OTUzDhw/H\nvXv3EBgYiODgYFhYWGDcuHH1HiTDMAzTtEhNEJGRkQgMDMSBAwegr6+PCRMmgIiq3ckTwzAMTQON\nrwAAIABJREFU836T2sQkJyeHUaNGYevWrTAzMwMAWFhYNNlhR+vSxMQX8iHHk4Mcr+ldW6mugpIC\n5BTnwKCVARTkqnXvgWh/NYWuS9Ly0+B31Q/ZxdlQ4ClAUV4RRhpGsNazhrWeNTrpdoKivKKsw2SY\nZqdWTUxHjhxBYGAgBg8ejOHDh4tqEO8tPh/YuRN48wZQV8fDghf4u+AOLiil4FbRc/Ro0x3nnf6E\n2pNIICsLGDsWeE8eDBSSEEN2D0FcdhxyinOgq6oL89bmsDOwg62BLRxMHdDbuDdAxG1bdDRe3bmM\nkOPrkP8mB3JaraGgowvbj6ZhyMTFFdYvEArw78t/cTH2Ii4nXEZf475Y6LAQKjkFwIULAJ8Pfmkx\n7ipm4LhhFq4mXMWdlDvQVNaEiaYJTLVMYdjKEHpqetBV1UUHnQ4YZDYIWkJF0JMn2C33EEsuLsUn\ndp9gsNlglApLoZj2GunxiQhMuo0nmZEoEZRgX791cEiRBwoLgUmTZLCnK9p+dzt+vPwj+pv0x5B2\nQ2Cjb4OYrBg8efUEeBqBxYO+Q1u7/kAd+i+roKQEiI4GunSp/jIFBcDdu8DgwQCAccHjYK1rjQUO\nC6CjWrvRIZnmr8qL1Pn5+QgJCUFgYCAuXryITz/9FGPGjIGLi0tjxVgtldYgcnMBDw/uR9KjBygv\nDyfvBaFniR70EzMgp6KKvJJ8QCiARj9HyCkpAbduATNmALNnA23bNu7G1NBfD//ClvAtuDn9JgQk\nQFp+Gl5kvcDjV48RH3kLnssCYZbLQ+sCIXiqqsg1NcRZpQSY9naGnWkv5L9KRFpKFHQv3ERbl7HA\n2rVAu3YAuORj628LABhqMRQDzQbiYMRBpD29g9DdfChadsRzwWtEZsfAKaoUO/43A136uaKPcR+8\nKX2DpNwkqGz5HfIvYvHUri3uWmsiPiUCfY7exrR7hEIVeZTKA/Kz58Jk1hLg2jVg2zbufw0N4OVL\nwMgIhUX5KMzNRKqNCWye56L0/l28bK2A9IJ0dNDpgNYqrYHiYpC8PB68foy9D/YiPicevdr2Qm/j\n3uio2xGpeamIy45DQk4CcotzUVBagMLSQjiaO2JClwmiGiQRIfBxILbd3QYNZQ3oq+nDWMMYiwcs\nhoayBrfTBQLkBO1BzHdfwKqVGc77zcA/vGg8ff0UVtqWmHouA/Z/nUeeihzaZvHBMzTkkkReHoR5\nucga0he6Jy4ANam9CQRAYCAEPyxHaXIiwg6uh4vr/KprvhcvAp99BiQnA6mpKNJQhfZabXxi9wn+\nfvY3ZvWeBU9bT3TQ6QAleaUaf/8aAxEhOjMayvLKaNe6XYX3i/hFUJZXrlAbjs6IBl/IR2f9zpWu\nP684Dyl5KdBW1Ya2ijZKhaWIyojCs9fPkJiTCF01XRi2MoSZlhnsDO1qvR1CEiK7KBsZbzKQUZgB\n89bmaKPeptbrqw917oupTGZmJg4dOoSgoCBcuHCh3gKsD1I3MjYWcHXlzpy2bAEUFHA7+TYmH5mM\nyNmR4AHAy5coLSnC6KtfQb+VAXZ9vAu8mBhg0yZg3z6gUyfAwQHo35/7Qb94wf0bPhwYM6baMYY+\nD8WZmDNYPnh5vZ21FfOLYf2bNfaM3oPB7QZXnGHnTgiO/o2tU22w9tkOfGA9HBdiLyBoXBCGmA8R\nzcYX8mGxxgCP30yD1h+7gcWLgW+/xc2km5h+bDqezHrydp3Pn6Pwg4HY3FsI3z7F8LT1xFe9v4Ld\n/44AMTHA3r1v542IABwdgYULgbAw4OpVQEEB/E8m4e44B7zQBiZkGUHB/3fg77+BXr24xDxhAleD\nKykB/hsPJKutNr4+8w36++5Dijph5ygj6KrqIiYrBkYaRji4PQe6yZnYOVAdPO/p6GDRE3dT7yI8\n6RZSXkZDT9sYproWMNM0g2keD6bx2TCMe42b6feQYKiCiWO+h7auMbYeWIDWqVmYpOsIHo+HPEEh\nnrx+CgUh8Kn1RPCKioCDBxFLmbgwsS+mm7gCy5dziW3kSGDOHODGDZSEHEGvU2PwXb9F8Gw9EODz\nkSlXAudDbvhzUzz012yG/rSv3u6r0lLg66+B1FQumSgpAYqKgJwcIC8PXLkCaGgg1HswnpwPxKD7\nWZgx1wI/OK5AO612KOQXQutoKDq+yIGymQVgbMzV8E6eBH7/HQgIAEaPxv0Pu2HK31PwaOYjvMh6\nAd8rvgiLD0NiTiL6kBG+uMeDWYYAbV8XAwoK8PVxQnpxJor4RfAf6Q9LHUup30ciwtWEq3iR9QKv\n0uNQ+iIafEV5lLbWBDQ1McraDX1N+r5dQCDgPuPSUm47/9tWPoS4l3YflxOv4mriNVxPvA5VRVUU\nlhbir7F/wbmDs2gVJ6NPwvOwJzSUNODSwQUuHVzw6nU8rl/cC5UXCTDnq2PFh77gqakB6uqAgQHQ\npg33v5ISMgpeY2DAAFBpCUrzclCSnwMNoQKs1EzRUb0djFT0kUVvkMLPwo28CKz7ZC9GdhxZrd/n\n3ZS7WHh2IZ5nPkdOUQ4KSgugoaQBXTVdaChpoFRYisczH4slNiLCyP0jsc55HWwNbKtVTl3UW4Jo\nyiRu5IsXwMCBwHffcTWB/z6ExWcXQ0leCauGrhKbvaCkAE57ndDLqBdWD10NLRUtrjnj9m3g+nXg\nxg1AQQFo3x7Q1QU2b+YSkIpKlfEV8Yuw4HMzmBhYYrP+C6waugrePbzrfN3j5xs/IywuDMc8j0me\nYdIkwMkJmD4diTmJ+OPuH5jeYzostC0qznp4EhzNHTHDYATQty9w/Di+yzoEOZ4cVjut5maKiABc\nXIDvv0fpZ94oEZSgldJ/TXG5uYCVFXfGamPDNWkNH84dNOfO5eYpKeEOCqqqFWMtLq5WU0zejUtQ\nnzSVS+JychAIBYg7exCGU79C1NaV6HHkOninQoGuXbmz5qQk7rMvLQWEQu6gq60N2NoCtragkhKk\n/XsV/MgIKBcLIDRvB33bvpAzMeEKFAjALy3BgajD6GBog34dBiPa1giDYr/HszmRXO0lPBwYP56r\n9bRrBxw4AGho4HbybbgGuuLRzEfQUNbAsL3DMNBsIGyjc/Hh0gDoxr6EXGttrpyZM1H0/BmUv/gK\nvJISbn+UxSwQAJaWgIsL3A9NxEfmLvDy3ozbn32EBZrXUVBSAOcnhVi4NwYHh7XFDCNXKKSmcUli\n5UpAS4s72QkOxr5V7jgRfQKB4wLFd/+bPAgGOCDD0gjJ3dojVV8F/X85iAezxqHIZShuJt3EreRb\nOP/pefC+/x4IDuYOtIaG3IG3sBDPEv5Fblo8LLPloJFfinxDbcjxBVDJLYBCYQlK5AiKPHnIQw48\nPp8rWFmZ+10RgQQCCPglIKEQcgTIE/Dki7HQWrcZJpomuJpwFeOCx2HTh5vgaeeJX2/9il8urMbj\nXWpQjUsCXw4olSMo8oUoNjOBWpfuOPT6Ehzb9IOBnAaQnw+8esUl4VevuP1aRkkJUFUFqakBKirg\nKStzsSkqcp9FURFKkxOx+Osu+GXVnUq/o/kl+fj+wvc48OAv3PqnLTSGOAMLFkBDywDyctwjA0SE\nLv5d4D/SH47FbYHVqwELC9wz4mFU1EqMdfoKWz/aKr7iw4e5z1FXl0twrVtz25SdDeTkcL/Bsv/n\nzQOmTKny91Rp6ws1ExU2RSgkGjGCyNf3nclCavdLO7qfel/ietIL0snzkCdp+2nT/FPz6UXmC+mF\njhhBtGMHvS54TeuurqOAewF0NuZsxWUyMynCuTvltVIkGjGC7qXco/47+pNboJvE1cZkxlB2YXaV\n25z5JpP01+nTk1dPJM8gEBDp6xPFx1e5LiKifQ/2vY3J35/IxYWst1pTeFI4Ny0/n6hDB6Jdu6Sv\nZN06onHjuL+PHSPq3JmopKRa5ddIjx5EZ868fT12LNHmzW9fJyURnT1L9PQpUV7e2+mlpURv3khc\nZamglN6USH6PiCghO4HabGhD52LO0cCdA+mPO3+Iz5CWRvT771wZ5Sw4vYA8D3nSxIMTyf2gOwmE\nAuIL+BQy2JDujXUgIiLB1l8prZ0+aX3How3XNkiNoYRfQq39WlNKbgpRWBiRqSn3udy9S6SnR4Kb\nN8jjkAdNCJ5AAqFAfOGsLCINDfo+ZD6turSq4sq//ZZo5Ejut1Nm+3aijz8W7Z9e23rRvtMbiFq3\nJrp9m4shKIhoxw4K/Wkqzfi8LWWeOMx95/j8d4IvoZevYmnCXlfqvsWG7iaGV9i2UftHkechT3pd\n8Jqb+OoVkZER91n+51HaIzL52YSc9jiRzW82lLloDpG7O1FxMbcvsrLEPoOfr/9MU45MqbC5AgGf\nxgePp4kHJ1bcV1KUrl9HB3uq0KO0R1LneZn3ktr90o68/vaivHWriAYOJBo/nsjMjGj/frH9++ut\nX2nVdwO43+lPPxEtXUq37fSoQFOVQmyVqCgyQrTv6OuviczNif78k2jbNqJVq4gWLiTy8SHatIn7\nXR45QnTuHFF4OFF6erW2qbI00HwTxKFDRDY23JemnPCkcOr4a0cSlv8RSJCQnUCLziwibT9tarW6\nFVlssqB+O/rRvgf73s507hzxrTtST//uND54PH3696f0we4PSGetDm26sYn7UI8cIb6JMW0boEIx\nV48TmZgQEVFhaSGprlKlwtJCbl1Xr3LJzNub7lm3ph1j2lFxfo7U+PKL82nuybn0+bHPpW/E/ftE\nVlaVbmd5rwtek8YaDS6mkhIqNjejCTP13v545swh+uSTyldSUMD9oK9fJ7K0JAoNrXb5NfLbb9xB\ngYhLAgYG3MGhgZ1/cZ5arW5F3f/XnfgCftULEFFBSQG139yeHAIc3n7eRBQXc49eavAocvFnlKmp\nSJPW9aUbiTfIcL0hnY05K3Fdl+IuUc8/er6d4OlJ9Nln3Pfq0CEi4r5bA3cOpEVnFlVcwYgRtHZ2\nDzr69Kj49LNnuc/t1Svx6Xl5RNraXMIlogcvH9DGoaqUP/1TsdmCHgWR8Ubjyk+o/iMUCunPB3+S\nwXoDWnh6IeUX55NAKKDJhyfTyL9GUgn/nROKc+cqxBafHU8LTi+gnKf3iXR1iRISpJaXXpBOWr5a\nlPkmU2z6gtMLaMiuIVRUWlRlzG9Xlk6FrVRobqCX1Fm8j3rTgtMLiFJSiPT0uO8nEdHly0S9e3OJ\n4quviE6fpkLfnyhFg0evTv9NRERP05+SwXoDKszNpF3jOlCRljrRggVEAwYQffQRUUYG8QV8upF4\ng3wu+tD0kOlVHsuq0vISRG4uCUyM6cT2b2ll2Eqxs4OFpxfS8vPLq71eoVBIOUU5FJ0RTaHRoWS5\nxZJmn5hNxfxiyn6TRc9M1Wjbyo/FPqSU8yG0d6AGFWirEzk4kP+q0TTrn1ncGb2GBlEm90Xt9ns3\nupV0i0tiampECxaQ4Hd/GjtVlS7b61FaW02iEydE670cd5mc9jiR8UZjUl2lSvZ/2FNybrL04Dds\nIJo5s9rbSkTkEOBAodHcQT3kBw960cmQO+O5eJH7kWZkVL2SrVu5M8xRo2pUdo1kZRFpaXEHjWnT\niH78seHKesf+h/vp39R/a7RMYk4i5RRVTPhhP31OpTzQrg1TRAnnwosLZLjekGKzYivM/+3Zb8W/\nv0lJROrqXM2tnNcFr6njrx0p4F6A+Ap27KB/uqnR84znb6eVnaWfOyc5+C+/fLt/8/IoX0uNZm12\nIb6AT9cSrtGSs0vIYL0BPXj5oMr9UF5afhpNPjyZLDZZ0ITgCTRo5yAqKCmQPPOSJRVrN0REo0dz\nZ9JV8DzkSVtubhG9Dn4cTB02d6iQNKqjcLQrfT1aldILKp6h30q6RW03tOU+608+4Wpl5QmFRE+e\nEPn5ETk4EA0YQEt3fkI/XPiBiIhm/TOLvr/wPRERBT4KpImbB3G/4bVriQQCCnkWQjprdcjW35YW\nnF5AZr+Y0b2UezXehvJaVIJ4lPaIQj+2pf09Fckt0I367ehH357lPqSy5qWafpHLyyrMItf9ruQQ\n4ED9dvSj3QudSfjBB/RfAVwtwMiIMpctpEHfm9DC0wtJd60upeWncfP060d06RIREU0PmU6/hf9G\ndO8eV9shomfpz8h8kznlFOXQ57NMKctUnwQLF9APF36gNhva0F8P/6L47PjqVYmHDyc6fLhG27f6\n8mqac3IOERH139aXcq3bc1VaCwui48ert5LiYq7syMgalV1jn35KNH8+d4ZbncTVBAkFAkp5fLPC\n9F9u/ELd/9e9wgHTzt+OridcF585I6PigZOILsZeFK9tEFFu0gvKVgYJ8v9rdisqIho6lDsAS3Pv\nHnfWy+cTbdlC/DEfU6dfO1Frv9bU9feu9N257yjiVUT1NliCU9GnaNLhSZU3q5aUEPXpwzWzxMVx\n006f5po8CwulL/efi7EXydbfloRCIUVnRJP+On26k3yndgGfPEkxVnq05vIasckCoYD6bu9Lu/7d\nxf3GTU3FmzeleJz2mNpuaEtp+Wlvmw+JqwnqrtUVnSjEZMaQ/jp9upZwTbTsojOLanTCK0mLShC3\nTmyn/NatKO0F10aYXpBOHTZ3oF3/7qJbSbeo06+d6lwlEwgFtObyGlp8ZjEJi4u5L8L160RTp3Jt\n4/9Vx+Oz48likwX5XfF7u/CMGdwZNhH5h/uT91Fvrp33U67K/ueDP2lC8AQiIorOiKaOK/UoQ0OB\nvlzVX/TFqZaiIrHaSnXdT71P7Te3p5TcFNL206aSkL+J5OS4bWtqLl8mAoi++UbWkdQ7oVBIkw9P\nps9CPhNNS8hOIN21utVu2irmF5PGGg3KePM2ed5IvEHh1hpcW7VAQOThQTRmTMXrBe/q3Zu7pmRh\nQXT9Or0ueE3x2dW7tlVv4uOJvL25Zht7e6J27biYqkEoFJLVFiu6GHuRevyvB/1669fax8HnU3Fb\nA3JaaCDWHLbn/h7qs70PCV6nE3XpQnTwYLVXOWTXEBoQMIA+OSLehDv7xGxacXEFFfOLqfe23vTL\njV/E3r+ZeJNsfrOp/bZQC0sQdPEidyGonIhXEaS/Tp+c9jiJqm/1av16IhUVrrr7Tjt4UWmReEL6\n9VcuSRBXHe32ezeiL74g2sJVf+eenEtrr64VzX4l/gqFLZ5IwiFDJJ4lSnXxInfGVUNCoZBMfjah\n+afm06TDk7gy16/nmnSaGqGQO2AkV9LM9h7LLcqlDps70KEn3LWFP+78wX0mNfDhnx/SkYgjotfb\n726nPTP6EU2ezCXWgQOlXrQXs307kaEh1xYua6WlRBcuEP3vfzX6Tay7uo40fTVp3IFxdT5JpGXL\n6KCzMbnud6WfLv1EgY8CyWijEUVt8yNq25bbtzUoI/hxMMEHFWo1/6b+S2a/mNGck3Po48CPK8Qt\nEArIeKMxPU1/WutNaVkJQorQ6FCSXylPD18+rP/C8/KIdu7kzsiqEhZG1L8/Eb29UC3o2ZOrgRB3\nDeDCiwviy/D5RF27EgUHS15ncTHRvn1vL4YRES1bRrR0aW22hmYcm0HyK+Up+LGU8phGczPxJhms\nN6DEnET6OPBj8ZskqmHt1bX01YmvRK/nnZpHv4f8QKSoyDVrVreGmZfH1Uj//rtG5Tclr/Jf0ceB\nH1frDsEqPX9OfF0d2n3zD1r+zwL6buVgihhsQ9SpE9GVKzVeXQm/hIIeBUl8r8f/elC7X9pJvV4y\n+8TsCs1dNcESxH9E1wFkKSOD+6H9l0x6bbEjvooyUUEBlQpKqdXqVhIvZlJYGNcOXFCuTbqoiLsd\n1cyMOxM0MHj75ezblzvLqoWQZyGk9JMS5Rbl1mp5pn79dOknGrJrCGn6akq8MFqZ28m3qfPWzqLX\nTnucuJsQNm6s9M4fiVJSalaLbe4cHbk79VRVuSYvH59qXQ+pqZuJN6Xfyk7cTQ29tvWq9forO3ZW\nr1e3ZsKglYGsQwB0dABNTSA+HrCwgGuJBbJNMqCrpoYnLx/ARNMEmsqaFZcbMoR7eG3OHMDEBPj3\nX+DmTcDennsoq18/4MwZrg+pdeuAJ0+4J79rYbjlcJyafOpttxKMTH038DuciTkDG30b6Knp1WjZ\nHm164GX+S6TmpaKtRls8fvWYezr3mw9rHkgT73Km0e3cyT1w16OH5Ac/64nYk+cSDGo3SNSFjJkW\n17FqXHYcVBVUYahuWKeyZdJ9aXZ2NsaPH4/OnTvDxsYGt27dQmZmJpydndGxY0e4uLggOztbNL+v\nry+srKxgbW2NM2fOyCLk+mVnBzx6BAAYkq6Gp+24J5Fvp9zmOtWTZuNGrrNBPh/w8uKe3j11iksO\nAPeE86lTwLffcl2DVOMJb0mU5JUw1GJorZZl6p+8nDwOux/GDtcdtVp2iPkQXIy7iPSCdBQLimGk\nYdQAUbZAFhbc76wBk0N1KMgpwK2jG/5++jcA4FLcJfQP6I/L8Zfrvu46r6EW5s2bh48++giHDh0C\nn89HQUEBVq9eDWdnZyxevBhr166Fn58f/Pz8EBERgQMHDiAiIgLJyckYNmwYoqKimuSwp9VWliDc\n3NA5oRA79AsxEMCdlDvobVRJgjA1BQIDpb8PcDWK27e5jgmZZkO/lT70W+nXatmh5kNxIfYCjDSM\nYGtg2yS6d2fq19jOY7Hu+jqoKKjgh7Af8NfYvzCs/bA6r7fRj7I5OTm4cuUKvL29AQAKCgrQ0tLC\nsWPH4OXlBQDw8vLC0aNHAQAhISHw9PSEoqIizM3NYWlpifDw8MYOu3517Qo8fAgA0IuIQ2jrdBTx\ni3A75TZ6GfWq+/rNzIDOlfdeybQcTu2dcD72PNe8pN/wnb8xjc+pvRP+Tf0Xm29txtVpV+slOQAy\nSBCxsbHQ19fHtGnT0LNnT3z++ecoKChAWloaDA259jJDQ0OkpaUBAFJSUmBS1mkaABMTEyQnJzd2\n2PWrrAZRWAi5qCgU2XTE7eTbeJr+FN3bdJd1dEwz01mvMwpLC3E86nij9A7KND4VBRWcmHQCN6bf\ngJWuVb2tt9GbmPh8Pu7du4etW7eid+/emD9/Pvz8/MTm4fF4lVaDpb3n4+Mj+tvR0RGOjo71EXL9\ns7bmeoENDwc6dYKdWU/svL8THXU7Qk1RTdbRMc0Mj8fDUIuhCHwciKUDl8o6HKaBDGo3qFrzhYWF\nVXvo6EZPECYmJjAxMUHv3lxb+/jx4+Hr64s2bdrg5cuXaNOmDVJTU2FgwN1xZGxsjMT/xgMAgKSk\nJBgbG0tcd/kE0aQpKwMdOnDd9vbqBXujHlh4ZiEm2TWNUdKY5qcsQXQxqMEodEyz9O7J88qVK6XO\n2+hNTG3atIGpqSmioqIAAOfOnUOXLl3g6uqKPXv2AAD27NmD0aNHAwDc3NwQFBSEkpISxMbGIjo6\nGn369GnssOufnR13e2qvXuhl1AuF/MLKL1AzTB24dHCBrYFtjW+TZVo2mdzF9Ouvv2Ly5MkoKSlB\nhw4dsGvXLggEAri7uyMgIADm5uYIDg4GANjY2MDd3R02NjZQUFCAv79/87gLw84OCAoCevVCV8Mu\nUJBTqPwWV4apAzMtMzya+UjWYTDvmeY9olxTdvw4NwJZbi6grIx/ov7BCMsRotGmGIZhGkPLHXK0\nKcvIAH75BVi1qup5GYZhGghLEAzDMIxElR073+PHkRmGYZiGxBIEwzAMIxFLEAzDMIxELEEwDMMw\nErEEwTAMw0jEEgTDMAwjEUsQDMMwjEQsQTAMwzASsQTBMAzDSMQSBMMwDCMRSxAMwzCMRCxBMAzD\nMBKxBMEwDMNIxBIEwzAMIxFLEAzDMIxELEEwDMMwErEEwTAMw0jEEgTDMAwjEUsQDMMwjEQsQTAM\nwzASySxBCAQC9OjRA66urgCAzMxMODs7o2PHjnBxcUF2drZoXl9fX1hZWcHa2hpnzpyRVcgMwzAt\niswSxObNm2FjYwMejwcA8PPzg7OzM6KiouDk5AQ/Pz8AQEREBA4cOICIiAiEhoZi1qxZEAqFsgpb\nqrCwMFmHIPMYWnr5TSEGWZffFGJo6eXXZwwySRBJSUk4efIkPvvsMxARAODYsWPw8vICAHh5eeHo\n0aMAgJCQEHh6ekJRURHm5uawtLREeHi4LMKuVHP6UrDy398YZF1+U4ihpZdfnzHIJEF8/fXXWL9+\nPeTk3haflpYGQ0NDAIChoSHS0tIAACkpKTAxMRHNZ2JiguTk5MYNuBri4uJkHYLMY2jp5TeFGGRd\nflOIoaWXX58xNHqC+Oeff2BgYIAePXqIag/v4vF4oqYnae83Nc3pS8HKf39jkHX5TSGGll5+fcag\nUC9rqYHr16/j2LFjOHnyJIqKipCbm4spU6bA0NAQL1++RJs2bZCamgoDAwMAgLGxMRITE0XLJyUl\nwdjYuMJ6jYyMZJ44ZF1+U4ihpZffFGKQdflNIYaWXn5NYujWrZv0dZC00/hGcOnSJWzYsAHHjx/H\n4sWLoauri2+//RZ+fn7Izs6Gn58fIiIiMGnSJISHhyM5ORnDhg3D8+fPm8QHwDAM05w1eg3iXWUH\n+iVLlsDd3R0BAQEwNzdHcHAwAMDGxgbu7u6wsbGBgoIC/P39WXJgGIZpBDKtQTAMwzBNF3uSmmEY\nhpGIJQiGYRhGomaZIAoKCuDl5YUZM2Zg//79Monh2bNnmDlzpui6SmMjIixbtgxz587F3r17G718\ngHsKfuLEiZg1axYOHz7caOXGxsbis88+w4QJE0TTQkJCMGPGDHh4eODs2bONXn5YWBgGDRqEmTNn\n4tKlSw1avrQYkpKSMHbsWEyfPh1r165t0PIl7W9JMTVm+QB3bOjduzdOnDghkxiuXr2KmTNn4vPP\nP8eAAQMatHxJx6AaHxupGdq7dy/9888/REQ0ceJEmcYiEAhowoQJjV7ukSNHyMvLixYsWEDnz59v\n9PKJiDZu3EhXrlwhIiI3N7dGL3/8+PEVpmVlZdH06dMbvfxLly7RiBEja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251        "text": [
252         "<matplotlib.figure.Figure at 0x7f3053fc1b90>"
253        ]
254       }
255      ],
256      "prompt_number": 98
257     },
258     {
259      "cell_type": "markdown",
260      "metadata": {},
261      "source": [
262       "# Invariance after scaling"
263      ]
264     },
265     {
266      "cell_type": "code",
267      "collapsed": false,
268      "input": [
269       "invariance_data = {}\n",
270       "for b in options[\"built\"]:\n",
271       "    invariance_data[b] = scaling.TestInvariance(\"./\"+b, fps=100, x0 = 0.5, y0 = 0.5, w0 = 1e-6, h0 = 1e-6, xz=400, yz=300)\n",
272       "    "
273      ],
274      "language": "python",
275      "metadata": {},
276      "outputs": [],
277      "prompt_number": 191
278     },
279     {
280      "cell_type": "code",
281      "collapsed": false,
282      "input": [
283       "invariance_data.keys()"
284      ],
285      "language": "python",
286      "metadata": {},
287      "outputs": [
288       {
289        "metadata": {},
290        "output_type": "pyout",
291        "prompt_number": 187,
292        "text": [
293         "['path-single', 'double', 'single', 'cumul-double', 'cumul-single']"
294        ]
295       }
296      ],
297      "prompt_number": 187
298     },
299     {
300      "cell_type": "code",
301      "collapsed": false,
302      "input": [
303       "fig = figure(figsize=(6,4))\n",
304       "for b in invariance_data.keys():\n",
305       "    plot(invariance_data[b][\"accuracy\"][:,2], invariance_data[b][\"accuracy\"][:,4])\n",
306       "xscale(\"log\")\n",
307       "yscale(\"log\")\n",
308       "legend(scaling_data.keys(), loc=\"best\")\n",
309       "xlabel(\"Total scaling factor\")\n",
310       "ylabel(\"Accumulated Error\")\n",
311       "fig.savefig(\"../../sam/figures/cumulative_error_grid.pdf\", format=\"PDF\")"
312      ],
313      "language": "python",
314      "metadata": {},
315      "outputs": [
316       {
317        "metadata": {},
318        "output_type": "display_data",
319 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7qI4z9fR+whTVHNIZCeeoABG5qe2mEI00O60eBQVynlln640/7RFNX62FlsJHvS6qlU09QbHOLj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\nyOQgSZIkNSCTgyRJktTA/wOgbRbeVj3ezAAAAABJRU5ErkJggg==\n",
320        "text": [
321         "<matplotlib.figure.Figure at 0x7f3051f4b3d0>"
322        ]
323       }
324      ],
325      "prompt_number": 195
326     },
327     {
328      "cell_type": "code",
329      "collapsed": false,
330      "input": [
331       "for b in invariance_data:\n",
332       "    plot(1.0/invariance_data[b][\"accuracy\"][:,2], invariance_data[b][\"performance\"][:,3])\n",
333       "xscale(\"log\")\n",
334       "legend(invariance_data.keys())\n",
335       "xlabel(\"Magnification\")\n",
336       "ylabel(\"Average FPS (100 frames)\")"
337      ],
338      "language": "python",
339      "metadata": {},
340      "outputs": [
341       {
342        "metadata": {},
343        "output_type": "pyout",
344        "prompt_number": 118,
345        "text": [
346         "<matplotlib.text.Text at 0x7f30539630d0>"
347        ]
348       },
349       {
350        "metadata": {},
351        "output_type": "display_data",
352 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eUt/s0aU7jdECat59SAGE7f0uBtJo5K5N4tVzn4mwiGe52lXtvUy9Tr9RwQF8e9jTyhjJoadtkV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\nCPfSYrMCg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C0XaxckyZPg7++PYba22Jyf32TaeXt7oKKiIV8CmMJcd4pAKIDYRYyq+KoO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\ntfLWlxr49ymTQ4eI1NSIsrJo/un59MPZH/g6qZJUhY40nrw8IgMD+nZee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bf1\n+L81rQcAEydORHR0NF588UUEBgZixYoVAIClS5di1KhRePnll+Ht7c1/Li4uDsuXL+eHGKtZWFhg\nw4YNmDZtGvz8/GBmZobk5OQu8xGiTzQ0mBANHjx4gJaWFlhYWODixYsIDw+HSqWCmZmZ0NEIESX6\nyyBEg6amJrz66qtoaWkBYwyrV6+mQkJIF+jKhBBCiNaoz4QQQojWqJgQQgjRGhUTQgghWqNiQggh\nRGtUTAghhGiNigkhhBCt/T+skvwVw4v4LwAAAABJRU5ErkJggg==\n",
353        "text": [
354         "<matplotlib.figure.Figure at 0x7f30537655d0>"
355        ]
356       }
357      ],
358      "prompt_number": 118
359     },
360     {
361      "cell_type": "markdown",
362      "metadata": {},
363      "source": [
364       "## Time to render frames\n",
365       "\n",
366       "Compare CPU and GPU frame rates for test image and fixed bounds"
367      ]
368     },
369     {
370      "cell_type": "code",
371      "collapsed": false,
372      "input": [
373       "def time_vs_frames(exec_name, bounds = [0.,0.,1.,1.], min_frames=0, \\\n",
374       "                    max_frames=100, step=10,test_image=\"svg-tests/rabbit_simple.svg\"):\n",
375       "    binname = options[\"local_bin\"]+exec_name\n",
376       "    data = []\n",
377       "    p = ProgressBar(sum(xrange(min_frames, max_frames, step)))\n",
378       "    display(\"Time VS Frames for %s\" % exec_name)\n",
379       "    p.animate(0)\n",
380       "    i = 0\n",
381       "    for frames in xrange(min_frames, max_frames+step, step):\n",
382       "        pt = [frames]\n",
383       "        # -l means to turn off lazy rendering\n",
384       "        # -Q means don't show the window\n",
385       "        cmd = binname + \" -l -Q -b %s %s %s %s -f %d %s\" % tuple(map(str, bounds) + [frames, test_image])\n",
386       "        \n",
387       "        # Everything on GPU\n",
388       "        start = time.time()\n",
389       "        os.system(cmd + \" -r gpu -T gpu\")\n",
390       "        end = time.time()\n",
391       "        pt += [(end - start)]\n",
392       "                \n",
393       "        # Everything on CPU\n",
394       "        start = time.time()\n",
395       "        os.system(cmd + \" -r cpu -T cpu\")\n",
396       "        end = time.time()\n",
397       "        pt += [(end - start)]\n",
398       "        \n",
399       "        data += [pt]\n",
400       "        i += frames\n",
401       "        p.animate(i)\n",
402       "        \n",
403       "    return asarray(data)"
404      ],
405      "language": "python",
406      "metadata": {},
407      "outputs": [],
408      "prompt_number": 7
409     },
410     {
411      "cell_type": "code",
412      "collapsed": false,
413      "input": [
414       "def plot_time_vs_frames(tf, new_figure=True):\n",
415       "    if new_figure:\n",
416       "        figure(figsize=(9,7))\n",
417       "        yscale('linear')\n",
418       "        xscale('linear')\n",
419       "        legend([\"GPU\", \"CPU\"])\n",
420       "        xlabel(\"Frames\")\n",
421       "        ylabel(\"Time To Render\")\n",
422       "        title(\"Quick, to the TARDIS of Infinite Precision!\")    \n",
423       "        \n",
424       "    plot(tf[:,0], tf[:,1], 'o-')\n",
425       "    plot(tf[:,0], tf[:,2], 'x-')\n",
426       "    "
427      ],
428      "language": "python",
429      "metadata": {},
430      "outputs": [],
431      "prompt_number": 8
432     },
433     {
434      "cell_type": "code",
435      "collapsed": false,
436      "input": [
437       "for p in options[\"built\"]:\n",
438       "    plot_time_vs_frames(time_vs_frames(p, bounds=[0.5,0.5,1e-14,1e-14]), False)"
439      ],
440      "language": "python",
441      "metadata": {},
442      "outputs": [
443       {
444        "metadata": {},
445        "output_type": "display_data",
446        "text": [
447         "'Time VS Frames for single'"
448        ]
449       },
450       {
451        "output_type": "stream",
452        "stream": "stdout",
453        "text": [
454         "\r",
455         "[                  0%                  ]"
456        ]
457       },
458       {
459        "output_type": "stream",
460        "stream": "stdout",
461        "text": [
462         " \r",
463         "[                  0%                  ]  1 of 450 complete"
464        ]
465       },
466       {
467        "output_type": "stream",
468        "stream": "stdout",
469        "text": [
470         " \r",
471         "[                  0%                  ]  1 of 450 complete"
472        ]
473       },
474       {
475        "output_type": "stream",
476        "stream": "stdout",
477        "text": [
478         " \r",
479         "[*                 2%                  ]  11 of 450 complete"
480        ]
481       },
482       {
483        "output_type": "stream",
484        "stream": "stdout",
485        "text": [
486         " \r",
487         "[***               7%                  ]  31 of 450 complete"
488        ]
489       },
490       {
491        "output_type": "stream",
492        "stream": "stdout",
493        "text": [
494         " \r",
495         "[*****            14%                  ]  61 of 450 complete"
496        ]
497       },
498       {
499        "output_type": "stream",
500        "stream": "stdout",
501        "text": [
502         " \r",
503         "[********         22%                  ]  101 of 450 complete"
504        ]
505       },
506       {
507        "output_type": "stream",
508        "stream": "stdout",
509        "text": [
510         " \r",
511         "[*************    34%                  ]  151 of 450 complete"
512        ]
513       },
514       {
515        "output_type": "stream",
516        "stream": "stdout",
517        "text": [
518         " \r",
519         "[*****************47%                  ]  211 of 450 complete"
520        ]
521       },
522       {
523        "output_type": "stream",
524        "stream": "stdout",
525        "text": [
526         " \r",
527         "[*****************62%****              ]  281 of 450 complete"
528        ]
529       },
530       {
531        "output_type": "stream",
532        "stream": "stdout",
533        "text": [
534         " \r",
535         "[*****************80%**********        ]  361 of 450 complete"
536        ]
537       },
538       {
539        "output_type": "stream",
540        "stream": "stdout",
541        "text": [
542         " \r",
543         "[****************100%******************]  451 of 450 complete"
544        ]
545       },
546       {
547        "metadata": {},
548        "output_type": "display_data",
549        "text": [
550         "'Time VS Frames for double'"
551        ]
552       },
553       {
554        "output_type": "stream",
555        "stream": "stdout",
556        "text": [
557         " \r",
558         "[                  0%                  ]"
559        ]
560       },
561       {
562        "output_type": "stream",
563        "stream": "stdout",
564        "text": [
565         " \r",
566         "[                  0%                  ]  1 of 450 complete"
567        ]
568       },
569       {
570        "output_type": "stream",
571        "stream": "stdout",
572        "text": [
573         " \r",
574         "[                  0%                  ]  1 of 450 complete"
575        ]
576       },
577       {
578        "output_type": "stream",
579        "stream": "stdout",
580        "text": [
581         " \r",
582         "[*                 2%                  ]  11 of 450 complete"
583        ]
584       },
585       {
586        "output_type": "stream",
587        "stream": "stdout",
588        "text": [
589         " \r",
590         "[***               7%                  ]  31 of 450 complete"
591        ]
592       },
593       {
594        "output_type": "stream",
595        "stream": "stdout",
596        "text": [
597         " \r",
598         "[*****            14%                  ]  61 of 450 complete"
599        ]
600       },
601       {
602        "output_type": "stream",
603        "stream": "stdout",
604        "text": [
605         " \r",
606         "[********         22%                  ]  101 of 450 complete"
607        ]
608       },
609       {
610        "output_type": "stream",
611        "stream": "stdout",
612        "text": [
613         " \r",
614         "[*************    34%                  ]  151 of 450 complete"
615        ]
616       },
617       {
618        "output_type": "stream",
619        "stream": "stdout",
620        "text": [
621         " \r",
622         "[*****************47%                  ]  211 of 450 complete"
623        ]
624       },
625       {
626        "output_type": "stream",
627        "stream": "stdout",
628        "text": [
629         " \r",
630         "[*****************62%****              ]  281 of 450 complete"
631        ]
632       },
633       {
634        "output_type": "stream",
635        "stream": "stdout",
636        "text": [
637         " \r",
638         "[*****************80%**********        ]  361 of 450 complete"
639        ]
640       },
641       {
642        "output_type": "stream",
643        "stream": "stdout",
644        "text": [
645         " \r",
646         "[****************100%******************]  451 of 450 complete"
647        ]
648       },
649       {
650        "metadata": {},
651        "output_type": "display_data",
652        "text": [
653         "'Time VS Frames for GMPrat'"
654        ]
655       },
656       {
657        "output_type": "stream",
658        "stream": "stdout",
659        "text": [
660         " \r",
661         "[                  0%                  ]"
662        ]
663       },
664       {
665        "output_type": "stream",
666        "stream": "stdout",
667        "text": [
668         " \r",
669         "[                  0%                  ]  1 of 450 complete"
670        ]
671       },
672       {
673        "output_type": "stream",
674        "stream": "stdout",
675        "text": [
676         " \r",
677         "[                  0%                  ]  1 of 450 complete"
678        ]
679       },
680       {
681        "output_type": "stream",
682        "stream": "stdout",
683        "text": [
684         " \r",
685         "[*                 2%                  ]  11 of 450 complete"
686        ]
687       },
688       {
689        "output_type": "stream",
690        "stream": "stdout",
691        "text": [
692         " \r",
693         "[***               7%                  ]  31 of 450 complete"
694        ]
695       },
696       {
697        "output_type": "stream",
698        "stream": "stdout",
699        "text": [
700         " \r",
701         "[*****            14%                  ]  61 of 450 complete"
702        ]
703       },
704       {
705        "output_type": "stream",
706        "stream": "stdout",
707        "text": [
708         " \r",
709         "[********         22%                  ]  101 of 450 complete"
710        ]
711       },
712       {
713        "output_type": "stream",
714        "stream": "stdout",
715        "text": [
716         " \r",
717         "[*************    34%                  ]  151 of 450 complete"
718        ]
719       },
720       {
721        "output_type": "stream",
722        "stream": "stdout",
723        "text": [
724         " \r",
725         "[*****************47%                  ]  211 of 450 complete"
726        ]
727       },
728       {
729        "output_type": "stream",
730        "stream": "stdout",
731        "text": [
732         " \r",
733         "[*****************62%****              ]  281 of 450 complete"
734        ]
735       },
736       {
737        "output_type": "stream",
738        "stream": "stdout",
739        "text": [
740         " \r",
741         "[*****************80%**********        ]  361 of 450 complete"
742        ]
743       },
744       {
745        "output_type": "stream",
746        "stream": "stdout",
747        "text": [
748         " \r",
749         "[****************100%******************]  451 of 450 complete"
750        ]
751       },
752       {
753        "output_type": "stream",
754        "stream": "stdout",
755        "text": [
756         "\n"
757        ]
758       },
759       {
760        "metadata": {},
761        "output_type": "display_data",
762 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KX4+99kth9wrbaCnJwnUas3MnTom/j6Xtkr4VFZmXxs7vSBPnNBSGft2TOekJD/olBc3uY2aXV1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\nfBjbLZuwfLKVfEU3svpPIF+7D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763        "text": [
764         "<matplotlib.figure.Figure at 0x7f252628efd0>"
765        ]
766       }
767      ],
768      "prompt_number": 9
769     },
770     {
771      "cell_type": "markdown",
772      "metadata": {},
773      "source": [
774       "## Precision of rendering\n",
775       "\n",
776       "Compare images"
777      ]
778     },
779     {
780      "cell_type": "code",
781      "collapsed": false,
782      "input": [
783       "def rgb2gray(rgb):\n",
784       "    return np.dot(rgb[...,:3], [0.299/256., 0.587/256., 0.144/256.])"
785      ],
786      "language": "python",
787      "metadata": {},
788      "outputs": [],
789      "prompt_number": 10
790     },
791     {
792      "cell_type": "code",
793      "collapsed": false,
794      "input": [
795       "def bmpdiff(img1, img2):\n",
796       "    p = subprocess.Popen(\"./bmpdiff %s %s\" % (img1, img2), bufsize=0, stdin=subprocess.PIPE, \\\n",
797       "                         stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)\n",
798       "    out = p.stdout.readlines()\n",
799       "    if len(out) != 1:\n",
800       "        raise Exception(\"bmpdiff %s %s failed: %s \" % (img1, img2, str(map(lambda e : e.strip(\"\\n\"),p.stderr.readlines()))))\n",
801       "    result = map(float, out[0].strip(\" \\r\\n\").split(\"\\t\"))\n",
802       "    for i in xrange(len(result)):\n",
803       "        if isnan(result[i]):\n",
804       "            result[i] = 0\n",
805       "    return result"
806      ],
807      "language": "python",
808      "metadata": {},
809      "outputs": [],
810      "prompt_number": 11
811     },
812     {
813      "cell_type": "code",
814      "collapsed": false,
815      "input": [
816       "def precision_vs_zoom(exec_name, xy, start_dims, end_dims, steps, test_image=\"svg-tests/rabbit_simple.svg\", show_outputs=False):\n",
817       "    binname = options[\"local_bin\"]+exec_name\n",
818       "    data = []\n",
819       "    bounds = [xy[0], xy[1], start_dims[0], start_dims[1]]\n",
820       "    dw = float(end_dims[0] - start_dims[0])/float(steps)\n",
821       "    dh = float(end_dims[1] - start_dims[1])/float(steps)\n",
822       "    p = ProgressBar(steps)\n",
823       "    display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
824       "    p.animate(0)\n",
825       "    im = None\n",
826       "    figure(figsize=(10,10))\n",
827       "    for i in xrange(steps+1):\n",
828       "       \n",
829       "        cmd = binname + \" -l -b %s %s %s %s %s\" % tuple(map(str, bounds) + [test_image])\n",
830       "        \n",
831       "        # Don't show the windows\n",
832       "        os.system(cmd + \" -Q -r gpu -T gpu -o gpu%d.bmp\" % i)\n",
833       "        os.system(cmd + \" -Q -r cpu -T cpu -o cpu%d.bmp\" % i)\n",
834       "        \n",
835       "        pt = [i]\n",
836       "        pt += bounds\n",
837       "        pt += [bmpdiff(\"gpu\"+str(i)+\".bmp\", \"gpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
838       "        pt += [bmpdiff(\"gpu\"+str(i)+\".bmp\", \"gpu0.bmp\")[3]]\n",
839       "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
840       "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu0.bmp\")[3]]\n",
841       "        pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"gpu\"+str(i)+\".bmp\")[3]]\n",
842       "\n",
843       "        if show_outputs != False:\n",
844       "            clear_output()\n",
845       "            if i == 0:\n",
846       "                im = imshow(imread(\"cpu0.bmp\"), cmap=get_cmap(\"gray\"))\n",
847       "            else:\n",
848       "                im.set_data(imread(\"cpu\"+str(i)+\".bmp\"))\n",
849       "                draw()\n",
850       "            title(\"Bounds: %s\" % str(bounds))\n",
851       "            \n",
852       "        display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
853       "        p.animate(i)\n",
854       "        \n",
855       "        if show_outputs != False:\n",
856       "            display(gcf())        \n",
857       "            \n",
858       "        \n",
859       "        # [step, x, y, w, h, gpu_delta, gpu_total_delta, cpu_delta, cpu_total_delta, gpu_vs_cpu\n",
860       "        data += [pt]\n",
861       "        bounds[2] += dw\n",
862       "        bounds[3] += dh\n",
863       "\n",
864       "        \n",
865       "    close(gcf())\n",
866       "    return asarray(data)"
867      ],
868      "language": "python",
869      "metadata": {},
870      "outputs": [],
871      "prompt_number": 12
872     },
873     {
874      "cell_type": "code",
875      "collapsed": false,
876      "input": [
877       "pz = precision_vs_zoom(\"single\", [0.5,0.5],[1e-5,1e-5],[1e-6,1e-6], 100, \"svg-tests/fox-vector.svg\", show_outputs=True)"
878      ],
879      "language": "python",
880      "metadata": {},
881      "outputs": [
882       {
883        "ename": "NameError",
884        "evalue": "name 'precision_vs_zoom' is not defined",
885        "output_type": "pyerr",
886        "traceback": [
887         "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
888         "\u001b[1;32m<ipython-input-1-177c6c5e9c41>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mpz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprecision_vs_zoom\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"single\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0.5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1e-5\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1e-5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1e-6\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1e-6\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m100\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"svg-tests/fox-vector.svg\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshow_outputs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
889         "\u001b[1;31mNameError\u001b[0m: name 'precision_vs_zoom' is not defined"
890        ]
891       }
892      ],
893      "prompt_number": 1
894     },
895     {
896      "cell_type": "code",
897      "collapsed": false,
898      "input": [
899       "pzd = precision_vs_zoom(\"double\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 1, \"svg-tests/fox-vector.svg\", show_outputs=True)"
900      ],
901      "language": "python",
902      "metadata": {},
903      "outputs": [
904       {
905        "metadata": {},
906        "output_type": "display_data",
907        "text": [
908         "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using double'"
909        ]
910       },
911       {
912        "output_type": "stream",
913        "stream": "stdout",
914        "text": [
915         " \r",
916         "[****************100%******************]  1 of 1 complete"
917        ]
918       },
919       {
920        "metadata": {},
921        "output_type": "display_data",
922 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QAA4BBhCwAAwCHCFgAAgEOELQAAAIcIWwAAAA55zMzO+k49HgVgt0CDu+CCC07aVllZqdatW5/F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\nQ4QtAAAAh/4XJX37efghybUAAAAASUVORK5CYII=\n",
923        "text": [
924         "<matplotlib.figure.Figure at 0x7f2525984e50>"
925        ]
926       },
927       {
928        "output_type": "stream",
929        "stream": "stdout",
930        "text": [
931         "\n"
932        ]
933       }
934      ],
935      "prompt_number": 16
936     },
937     {
938      "cell_type": "code",
939      "collapsed": false,
940      "input": [
941       "pzgmp = precision_vs_zoom(\"GMPrat\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 1, \"svg-tests/fox-vector.svg\", show_outputs=True)\n",
942       "# Need to adapt mpfrc++ for required precision. Probably not worth it, just go back to mpfr?"
943      ],
944      "language": "python",
945      "metadata": {},
946      "outputs": [
947       {
948        "metadata": {},
949        "output_type": "display_data",
950        "text": [
951         "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using GMPrat'"
952        ]
953       },
954       {
955        "output_type": "stream",
956        "stream": "stdout",
957        "text": [
958         " \r",
959         "[****************100%******************]  1 of 1 complete"
960        ]
961       },
962       {
963        "metadata": {},
964        "output_type": "display_data",
965 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4XonaWv6wYQEZF2PHjwAKampq9Vxv79+5Gbm4vt27djxYoV6NatWxG1juj9wZ4tIqJi6MyZM5g2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\n",
966        "text": [
967         "<matplotlib.figure.Figure at 0x7f25259b5450>"
968        ]
969       },
970       {
971        "output_type": "stream",
972        "stream": "stdout",
973        "text": [
974         "\n"
975        ]
976       }
977      ],
978      "prompt_number": 17
979     },
980     {
981      "cell_type": "code",
982      "collapsed": false,
983      "input": [
984       "def plot_precision_vs_zoom(pz, gpu=True):\n",
985       "    figure(figsize=(9,7))\n",
986       "    if gpu:\n",
987       "        plot(pz[:,3], pz[:,6], 'o-')\n",
988       "        legend([\"GPU\", \"CPU\"])\n",
989       "        \n",
990       "    yscale('log')\n",
991       "    xscale('log')\n",
992       "    plot(pz[:,3], pz[:,8], 'o-')\n",
993       "    xlabel(\"Width\")\n",
994       "    ylabel(\"Average distance to closest pixel in original\")\n",
995       "    title(\"Arr Captain We Be Sinking Into The Sea of Precision\")"
996      ],
997      "language": "python",
998      "metadata": {},
999      "outputs": [],
1000      "prompt_number": 454
1001     },
1002     {
1003      "cell_type": "code",
1004      "collapsed": false,
1005      "input": [
1006       "plot_precision_vs_zoom(pz)"
1007      ],
1008      "language": "python",
1009      "metadata": {},
1010      "outputs": [
1011       {
1012        "metadata": {},
1013        "output_type": "display_data",
1014 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Cl4+vTpmDlzJszMzJCUlISpU6fi8ccf10dsRERERFrROOQ0aNAgHD16FDKZDKmpqSplhsIhJyIi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\n",
1015        "text": [
1016         "<matplotlib.figure.Figure at 0x7f94baa28290>"
1017        ]
1018       }
1019      ],
1020      "prompt_number": 384
1021     },
1022     {
1023      "cell_type": "code",
1024      "collapsed": false,
1025      "input": [
1026       "plot_precision_vs_zoom(pzd, False)"
1027      ],
1028      "language": "python",
1029      "metadata": {},
1030      "outputs": [
1031       {
1032        "metadata": {},
1033        "output_type": "display_data",
1034 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tWr8PHxMVmHpiRHkgMAhYXSbsk//CCdfRXC71uT2rQJGDcOWL4ccHBIQmzsTuTnO0KlUuHEiR44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\n+yAnvW50tPjVvpIjiY1NQUREhsOBg8BCVFaKthRLl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1035        "text": [
1036         "<matplotlib.figure.Figure at 0x7f94bae39bd0>"
1037        ]
1038       }
1039      ],
1040      "prompt_number": 455
1041     },
1042     {
1043      "cell_type": "code",
1044      "collapsed": false,
1045      "input": [],
1046      "language": "python",
1047      "metadata": {},
1048      "outputs": []
1049     }
1050    ],
1051    "metadata": {}
1052   }
1053  ]
1054 }

UCC git Repository :: git.ucc.asn.au